diff --git a/etl/steps/archive/garden/agriculture/2023-04-21/uk_long_term_yields.meta.yml b/etl/steps/archive/garden/agriculture/2023-04-21/uk_long_term_yields.meta.yml index cad6d14caa9..f6fc66d533f 100644 --- a/etl/steps/archive/garden/agriculture/2023-04-21/uk_long_term_yields.meta.yml +++ b/etl/steps/archive/garden/agriculture/2023-04-21/uk_long_term_yields.meta.yml @@ -5,7 +5,7 @@ dataset: • Data from 1270 to 1870 is taken from Table 3.06 of Broadberry et al. (2015). The data in this table is based on the Medieval Accounts Database, the Early Modern Probate Inventories Database and the Modern Farm Accounts Database. Seed sown per acre from the Medieval and Modern Databases. Pulses for the modern period and all seeds sown for the early modern period are taken from Overton and Campbell (1996), Allen (2005). This comprises crop yield estimates only for England. For this dataset, we have assumed that yields in England are also representative of average UK yields. The data was given as decadal averages, and we have assumed, for each value, the middle year in each decade. - All values of yield in bushels per acre have been converted to tonnes per hectare, using the conversion factors given by the USDA for the different commodities. + All values of yield in bushels per acre have been converted to tonnes per hectare, using the conversion factors given by [the USDA](https://www.ers.usda.gov/webdocs/publications/41880/33132_ah697_002.pdf) for the different commodities. • Data from 1870 to 1960 is taken from Table 4 of Brassley (2000). The data in this table is based on the book "A hundred Years of British food and farming: a statistical survey", by H. F. Marks (ed. D. K. Britton, 1989). The data is provided over 5-year periods. We have assumed, for each value, the middle year in each 5-year set. diff --git a/etl/steps/archive/garden/bp/2022-07-11/statistical_review.meta.yml b/etl/steps/archive/garden/bp/2022-07-11/statistical_review.meta.yml index 43544c0466d..cb5f9df1ae4 100644 --- a/etl/steps/archive/garden/bp/2022-07-11/statistical_review.meta.yml +++ b/etl/steps/archive/garden/bp/2022-07-11/statistical_review.meta.yml @@ -10,9 +10,9 @@ dataset: date_accessed: 2021-07-08 url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -38,4 +38,4 @@ dataset: * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). diff --git a/etl/steps/archive/garden/bp/2022-07-14/energy_mix.meta.yml b/etl/steps/archive/garden/bp/2022-07-14/energy_mix.meta.yml index 2a7cdcbfc45..df15ba6753e 100644 --- a/etl/steps/archive/garden/bp/2022-07-14/energy_mix.meta.yml +++ b/etl/steps/archive/garden/bp/2022-07-14/energy_mix.meta.yml @@ -10,9 +10,9 @@ dataset: date_accessed: 2022-07-08 url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -38,9 +38,9 @@ dataset: * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). description: | - Raw data on energy consumption is sourced from the BP Statistical Review of World Energy. + Raw data on energy consumption is sourced from [the BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). Primary energy in exajoules (EJ) has been converted to TWh by Our World in Data based on a conversion factor of 1,000,000 / 3,600 (~277.778). @@ -48,11 +48,11 @@ dataset: Also, for non-fossil based electricity, there are two ways to define primary energy: * One is "direct primary energy", which corresponds to the electricity generation (in TWh). * The other is "input-equivalent primary energy" (also called "primary energy using the substitution method"). - This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in BP's methodology document. For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. + This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in [BP's methodology document](https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2022-methodology.pdf). For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. Additional metrics have been calculated by Our World in Data: – Annual change in energy consumption by source: this is calculated as the difference from the previous year. – % of total primary energy: calculated as each source's share of primary energy (direct energy and primary energy using the substitution method) from all sources. – Per capita energy by source: calculated as primary energy consumption by source, divided by population. - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). diff --git a/etl/steps/archive/garden/bp/2022-07-14/statistical_review.meta.yml b/etl/steps/archive/garden/bp/2022-07-14/statistical_review.meta.yml index 2f0d0a72c4a..66ca1356bab 100644 --- a/etl/steps/archive/garden/bp/2022-07-14/statistical_review.meta.yml +++ b/etl/steps/archive/garden/bp/2022-07-14/statistical_review.meta.yml @@ -10,9 +10,9 @@ dataset: date_accessed: 2022-07-08 url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -38,4 +38,4 @@ dataset: * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). diff --git a/etl/steps/archive/garden/bp/2022-12-28/energy_mix.meta.yml b/etl/steps/archive/garden/bp/2022-12-28/energy_mix.meta.yml index 6194cbd2c3e..2d10be74f44 100644 --- a/etl/steps/archive/garden/bp/2022-12-28/energy_mix.meta.yml +++ b/etl/steps/archive/garden/bp/2022-12-28/energy_mix.meta.yml @@ -10,9 +10,9 @@ dataset: date_accessed: 2022-07-08 url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -38,9 +38,9 @@ dataset: * "North America" - All North American countries + "Other Caribbean" + "Other North America". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). description: | - Raw data on energy consumption is sourced from the BP Statistical Review of World Energy. + Raw data on energy consumption is sourced from [the BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). Primary energy in exajoules (EJ) has been converted to TWh by Our World in Data based on a conversion factor of 1,000,000 / 3,600 (~277.778). @@ -48,11 +48,11 @@ dataset: Also, for non-fossil based electricity, there are two ways to define primary energy: * One is "direct primary energy", which corresponds to the electricity generation (in TWh). * The other is "input-equivalent primary energy" (also called "primary energy using the substitution method"). - This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in BP's methodology document. For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. + This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in [BP's methodology document](https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2022-methodology.pdf). For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. Additional metrics have been calculated by Our World in Data: - Annual change in energy consumption by source: this is calculated as the difference from the previous year. - % of total primary energy: calculated as each source's share of primary energy (direct energy and primary energy using the substitution method) from all sources. - Per capita energy by source: calculated as primary energy consumption by source, divided by population. - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). diff --git a/etl/steps/archive/garden/bp/2022-12-28/statistical_review.meta.yml b/etl/steps/archive/garden/bp/2022-12-28/statistical_review.meta.yml index 73718ad6fc3..dc37f21437f 100644 --- a/etl/steps/archive/garden/bp/2022-12-28/statistical_review.meta.yml +++ b/etl/steps/archive/garden/bp/2022-12-28/statistical_review.meta.yml @@ -10,9 +10,9 @@ dataset: date_accessed: 2022-07-08 url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -38,7 +38,7 @@ dataset: * "North America" - All North American countries + "Other Caribbean" + "Other North America". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). tables: {} diff --git a/etl/steps/archive/garden/bp/2023-02-20/energy_mix.meta.yml b/etl/steps/archive/garden/bp/2023-02-20/energy_mix.meta.yml index fc23c52d6a4..0ded5ea0272 100644 --- a/etl/steps/archive/garden/bp/2023-02-20/energy_mix.meta.yml +++ b/etl/steps/archive/garden/bp/2023-02-20/energy_mix.meta.yml @@ -3,43 +3,75 @@ dataset: title: Energy mix (BP, 2023) short_name: energy_mix sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - BP's region definitions, denoted with "(BP)", are: - * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. - * "Australasia (BP)": Australia, New Zealand. - * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. - * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. - * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama - * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. - * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. - * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. - * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. - * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. - * "North America (BP)": US (excluding US territories), Canada, Mexico - * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. - * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. - * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. - * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. - * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. - * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. - - Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: - * "Africa" - All African countries + "Other Africa". - * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". - * "Europe" - All European countries + "Other Europe". - * "North America" - All North American countries + "Other Caribbean" + "Other North America". - * "Oceania" - All Oceanian countries. - * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + description: >- + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes + countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" + to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding + up (when possible) the contributions from the countries in the region. + + + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: + + * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, + North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. + + * "Australasia (BP)": Australia, New Zealand. + + * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. + + * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. + + * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama + + * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. + + * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. + + * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. + + * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. + + * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. + + * "North America (BP)": US (excluding US territories), Canada, Mexico + + * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. + + * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, + Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. + + * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. + + * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. + + * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. + + * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. + + + Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: + + * "Africa" - All African countries + "Other Africa". + + * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". + + * "Europe" - All European countries + "Other Europe". + + * "North America" - All North American countries + "Other Caribbean" + "Other North America". + + * "Oceania" - All Oceanian countries. + + * "South America" - All South American countries + "Other South America". + + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other + regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions + [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). description: | - Raw data on energy consumption is sourced from the BP Statistical Review of World Energy. + Raw data on energy consumption is sourced from [the BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). Primary energy in exajoules (EJ) has been converted to TWh by Our World in Data based on a conversion factor of 1,000,000 / 3,600 (~277.778). @@ -47,11 +79,11 @@ dataset: Also, for non-fossil based electricity, there are two ways to define primary energy: * One is "direct primary energy", which corresponds to the electricity generation (in TWh). * The other is "input-equivalent primary energy" (also called "primary energy using the substitution method"). - This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in BP's methodology document. For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. + This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in [BP's methodology document](https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2022-methodology.pdf). For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. Additional metrics have been calculated by Our World in Data: - Annual change in energy consumption by source: this is calculated as the difference from the previous year. - % of total primary energy: calculated as each source's share of primary energy (direct energy and primary energy using the substitution method) from all sources. - Per capita energy by source: calculated as primary energy consumption by source, divided by population. - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). diff --git a/etl/steps/archive/garden/demography/2022-11-30/life_expectancy.meta.yml b/etl/steps/archive/garden/demography/2022-11-30/life_expectancy.meta.yml index 434acc43d9d..571856518f6 100644 --- a/etl/steps/archive/garden/demography/2022-11-30/life_expectancy.meta.yml +++ b/etl/steps/archive/garden/demography/2022-11-30/life_expectancy.meta.yml @@ -2,310 +2,250 @@ dataset: namespace: demography short_name: life_expectancy title: Life Expectancy (various sources) - description: | + description: >- This dataset has been created using multiple sources. We use UN WPP for data since 1950 (estimates and medium variant) and a combination of other sources before this year. + For continents, we use UN's definitions for values after 1950 and Riley (2005) definitions for values prior to 1950. Note that Riley reports "Americas", while the UN reports "Northern America" and "Latin America and the Caribbean" separately. - SOURCES - World Population Prospects - UN (2022) - World Population Prospects 2022 is the 27th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. More details at https://population.un.org/wpp/Publications/. + **SOURCES** + + + **World Population Prospects - UN (2022)** + + World Population Prospects 2022 is the 27th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. + The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. + More details at https://population.un.org/wpp/Publications/. + + + **Life Tables - Human Mortality Database (2022-11-04)** + + To facilitate rapid downloads, the database has been organized into zipped data files. Two series of files are intended for different purposes and for different users. + For users who want to obtain all available data for an individual country or for all countries, the zipped data files labeled "By country" are recommended. The file + organization follows internal practices and is not particularly user-friendly, but all publicly-available HMD data are included in this set.For users who only want + information of a given kind for all countries, the files "By statistic" are recommended. In this case the file organization is simpler, but only certain parts of + the database (i.e., items labeled "Complete Data Series" on country pages) are available in this format. - Life Tables - Human Mortality Database (2022-11-04) - To facilitate rapid downloads, the database has been organized into zipped data files. Two series of files are intended for different purposes and for different users. For users who want to obtain all available data for an individual country or for all countries, the zipped data files labeled "By country" are recommended. The file organization follows internal practices and is not particularly user-friendly, but all publicly-available HMD data are included in this set.For users who only want information of a given kind for all countries, the files "By statistic" are recommended. In this case the file organization is simpler, but only certain parts of the database (i.e., items labeled "Complete Data Series" on country pages) are available in this format. More details can be found at https://www.mortality.org/Data/ExplanatoryNotes. - Life Expectancy at Birth (Total) - Zijdeman et al. (2015) + + **Life Expectancy at Birth (Total) - Zijdeman et al. (2015)** + This dataset provides Period Life Expectancy at birth per country and year. The overall aim of the dataset is to cover the entire world for the period 1500-2000. The current version (version 2) was build as part of the OECD "How was life" project. The dataset has nearly global coverage for the post 1950 period, while pre 1950 the coverage decreases the more historic the time period. Depending on sources, the data are annual estimates, 5 yearly or decadel estimates + The sources used are: - - UN World Population Project. - - http://www.mortality.org. - - http://www.gapminder.org. - - http://stats.oecd.org. - - Montevideo-Oxford Latin America Economic History Database. - - http://www.ons.gov.uk/ons/datasets-and-tables/index.html. - - http://www.abs.gov.au/ausstats/abs@.nsf/web+pages/statistics?opendocument#from-banner=LN. - - Kannisto, V., Nieminen, M. & Turpeinen, O. (1999). Finnish Life Tables since 1751, Demographic Research, 1(1), DOI: 10.4054/DemRes.1999.1.1 + + - [UN World Population Project](http://esa.un.org/wpp/). + + - [Human Mortality Database](http://www.mortality.org). + + - [Gapminder](http://www.gapminder.org). + + - [OECD](http://stats.oecd.org). + + - [Montevideo-Oxford Latin America Economic History Database](http://www.lac.ox.ac.uk/moxlad-database). + + - [ONS](http://www.ons.gov.uk/ons/datasets-and-tables/index.html). + + - [Australian Bureau of Statistics](http://www.abs.gov.au/ausstats/abs@.nsf/web+pages/statistics?opendocument#from-banner=LN). + + - Kannisto, V., Nieminen, M. & Turpeinen, O. (1999). Finnish Life Tables since 1751, Demographic Research, 1(1), DOI: 10.4054/DemRes.1999.1.1 + For specifics concerning (selections of) the sources, see the R-file below, with which the dataset was created. + Link to paper can be found at https://clio-infra.eu/docs/Total_life_expectancy.docx. licenses: - - name: CC BY 3.0 IGO - url: http://creativecommons.org/licenses/by/3.0/igo/ - - name: CC BY 4.0 - url: https://www.mortality.org/Data/UserAgreement - - name: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication License - url: https://datasets.iisg.amsterdam/dataset.xhtml?persistentId=hdl:10622/LKYT53 - - name: JSTOR - url: https://about.jstor.org/terms/ - version: "2022-11-30" + - name: CC BY 3.0 IGO + url: http://creativecommons.org/licenses/by/3.0/igo/ + - name: CC BY 4.0 + url: https://www.mortality.org/Data/UserAgreement + - name: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication License + url: https://datasets.iisg.amsterdam/dataset.xhtml?persistentId=hdl:10622/LKYT53 + - name: JSTOR + url: https://about.jstor.org/terms/ + version: '2022-11-30' sources: - - name: - United Nations, Department of Economic and Social Affairs, Population Division - (2022) - url: https://population.un.org/wpp/Download/ - owid_data_url: https://walden.nyc3.digitaloceanspaces.com/un/2022-07-11/un_wpp.zip - date_accessed: "2022-09-09" - publication_date: "2022-07-11" - publication_year: 2022 - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles - owid_data_url: https://walden.nyc3.digitaloceanspaces.com/hmd/2022-11-04/life_tables.zip - date_accessed: "2022-11-04" - publication_year: 2022 - - name: Zijdeman et al. (2015) (via clio-infra.eu) - url: https://clio-infra.eu/Indicators/LifeExpectancyatBirthTotal.html - source_data_url: https://clio-infra.eu/data/LifeExpectancyatBirth(Total)_Broad.xlsx - owid_data_url: https://walden.nyc3.digitaloceanspaces.com/papers/2022-11-01/zijdeman_et_al_2015.xlsx - date_accessed: "2022-11-01" - publication_year: 2015 - - name: Riley (2005) - url: https://doi.org/10.1111/j.1728-4457.2005.00083.x - source_data_url: https://u.demog.berkeley.edu/~jrw/Biblio/Eprints/%20P-S/riley.2005_estimates.global.e0.pdf - owid_data_url: https://walden.nyc3.digitaloceanspaces.com/papers/2022-11-01/riley_2005.pdf - date_accessed: "2022-11-01" - publication_date: "2005-10-21" - publication_year: 2005 + - name: United Nations, Department of Economic and Social Affairs, Population Division (2022) + url: https://population.un.org/wpp/Download/ + owid_data_url: https://walden.nyc3.digitaloceanspaces.com/un/2022-07-11/un_wpp.zip + date_accessed: '2022-09-09' + publication_date: '2022-07-11' + publication_year: 2022 + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles + owid_data_url: https://walden.nyc3.digitaloceanspaces.com/hmd/2022-11-04/life_tables.zip + date_accessed: '2022-11-04' + publication_year: 2022 + - name: Zijdeman et al. (2015) (via clio-infra.eu) + url: https://clio-infra.eu/Indicators/LifeExpectancyatBirthTotal.html + source_data_url: https://clio-infra.eu/data/LifeExpectancyatBirth(Total)_Broad.xlsx + owid_data_url: https://walden.nyc3.digitaloceanspaces.com/papers/2022-11-01/zijdeman_et_al_2015.xlsx + date_accessed: '2022-11-01' + publication_year: 2015 + - name: Riley (2005) + url: https://doi.org/10.1111/j.1728-4457.2005.00083.x + source_data_url: https://u.demog.berkeley.edu/~jrw/Biblio/Eprints/%20P-S/riley.2005_estimates.global.e0.pdf + owid_data_url: https://walden.nyc3.digitaloceanspaces.com/papers/2022-11-01/riley_2005.pdf + date_accessed: '2022-11-01' + publication_date: '2005-10-21' + publication_year: 2005 tables: historical: title: Life Expectancy (various sources) - Historical variables: life_expectancy_0_hist: title: Life expectancy at birth (historical) - description: - "The average number of years that a newborn could expect to live, - if he or she were to pass through life exposed to the sex- and age-specific - death rates prevailing at the time of his or her birth, for a specific year, - in a given country, territory, or geographic area. - - - Definition from the WHO. - - " + description: "The average number of years that a newborn could expect to live, if he or she were to pass through life + exposed to the sex- and age-specific death rates prevailing at the time of his or her birth, for a specific year, + in a given country, territory, or geographic area.\n\nDefinition from the WHO.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Zijdeman et al. (2015) - url: https://clio-infra.eu/Indicators/LifeExpectancyatBirthTotal.html - - name: Riley (2005) - url: https://doi.org/10.1111/j.1728-4457.2005.00083.x + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Zijdeman et al. (2015) + url: https://clio-infra.eu/Indicators/LifeExpectancyatBirthTotal.html + - name: Riley (2005) + url: https://doi.org/10.1111/j.1728-4457.2005.00083.x life_expectancy_15_hist: title: Life expectancy at 15 (historical) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 15 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 15 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles life_expectancy_65_hist: title: Life expectancy at 65 (historical) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 65 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 65 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles life_expectancy_80_hist: title: Life expectancy at 80 (historical) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 80 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 80 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles life_expectancy: title: Life Expectancy (various sources) variables: life_expectancy_0: title: Life expectancy at birth - description: - "The average number of years that a newborn could expect to live, - if he or she were to pass through life exposed to the sex- and age-specific - death rates prevailing at the time of his or her birth, for a specific year, - in a given country, territory, or geographic area. - - - Definition from the WHO. - - " + description: "The average number of years that a newborn could expect to live, if he or she were to pass through life + exposed to the sex- and age-specific death rates prevailing at the time of his or her birth, for a specific year, + in a given country, territory, or geographic area.\n\nDefinition from the WHO.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Zijdeman et al. (2015) - url: https://clio-infra.eu/Indicators/LifeExpectancyatBirthTotal.html - - name: Riley (2005) - url: https://doi.org/10.1111/j.1728-4457.2005.00083.x + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Zijdeman et al. (2015) + url: https://clio-infra.eu/Indicators/LifeExpectancyatBirthTotal.html + - name: Riley (2005) + url: https://doi.org/10.1111/j.1728-4457.2005.00083.x life_expectancy_15: title: Life expectancy at 15 - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 15 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 15 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles life_expectancy_65: title: Life expectancy at 65 - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 65 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 65 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles life_expectancy_80: title: Life expectancy at 80 - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 80 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 80 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles projection: title: Life Expectancy (various sources) - Projection variables: life_expectancy_0_proj: title: Life expectancy at birth (projection) - description: - "The average number of years that a newborn could expect to live, - if he or she were to pass through life exposed to the sex- and age-specific - death rates prevailing at the time of his or her birth, for a specific year, - in a given country, territory, or geographic area. - - - Definition from the WHO. - - " + description: "The average number of years that a newborn could expect to live, if he or she were to pass through life + exposed to the sex- and age-specific death rates prevailing at the time of his or her birth, for a specific year, + in a given country, territory, or geographic area.\n\nDefinition from the WHO.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ life_expectancy_15_proj: title: Life expectancy at 15 (projection) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 15 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 15 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ life_expectancy_65_proj: title: Life expectancy at 65 (projection) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 65 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 65 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ - - name: Human Mortality Database - url: https://www.mortality.org/Data/ZippedDataFiles + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ + - name: Human Mortality Database + url: https://www.mortality.org/Data/ZippedDataFiles life_expectancy_80_proj: title: Life expectancy at 80 (projection) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 80 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 80 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - name: UN WPP (2022) - url: https://population.un.org/wpp/Download/ + - name: UN WPP (2022) + url: https://population.un.org/wpp/Download/ diff --git a/etl/steps/archive/garden/eia/2022-07-27/energy_consumption.meta.yml b/etl/steps/archive/garden/eia/2022-07-27/energy_consumption.meta.yml index cf9b7d315fb..ea8551ecde8 100644 --- a/etl/steps/archive/garden/eia/2022-07-27/energy_consumption.meta.yml +++ b/etl/steps/archive/garden/eia/2022-07-27/energy_consumption.meta.yml @@ -4,24 +4,21 @@ dataset: title: Total energy consumption (EIA, 2022) short_name: energy_consumption description: | - Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their Bulk Download Facility. - - EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with our region definitions). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their [Bulk Download Facility](https://www.eia.gov/opendata/bulkfiles.php). + EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. sources: - - - name: Our World in Data based on EIA's total energy consumption (2022) - published_by: U.S. Energy Information Administration (EIA) - publication_year: 2022 - date_accessed: 2022-07-27 - url: https://www.eia.gov/opendata/bulkfiles.php - + - name: Our World in Data based on EIA's total energy consumption (2022) + published_by: U.S. Energy Information Administration (EIA) + publication_year: 2022 + date_accessed: 2022-07-27 + url: https://www.eia.gov/opendata/bulkfiles.php tables: energy_consumption: variables: - energy_consumption: - title: Total energy consumption (TWh) - short_unit: TWh - unit: terawatt-hours - display: - name: Total energy consumption + energy_consumption: + title: Total energy consumption (TWh) + short_unit: TWh + unit: terawatt-hours + display: + name: Total energy consumption diff --git a/etl/steps/archive/garden/ember/2022-12-13/yearly_electricity.meta.yml b/etl/steps/archive/garden/ember/2022-12-13/yearly_electricity.meta.yml index 27e8777d08d..2e8d5986346 100644 --- a/etl/steps/archive/garden/ember/2022-12-13/yearly_electricity.meta.yml +++ b/etl/steps/archive/garden/ember/2022-12-13/yearly_electricity.meta.yml @@ -4,19 +4,17 @@ dataset: title: Yearly Electricity Data (Ember, 2022) short_name: yearly_electricity description: | - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on Ember's Yearly Electricity Data (2022). - published_by: Ember - publication_year: 2022 - date_accessed: 2022-12-13 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - + - name: Our World in Data based on Ember's Yearly Electricity Data (2022). + published_by: Ember + publication_year: 2022 + date_accessed: 2022-12-13 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ tables: capacity: variables: @@ -132,38 +130,38 @@ tables: variables: clean__pct: title: Clean (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Clean fossil__pct: title: Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil gas_and_other_fossil__pct: title: Gas and Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas and Other Fossil hydro__bioenergy_and_other_renewables__pct: title: Hydro, Bioenergy and Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro, Bioenergy and Other Renewables renewables__pct: title: Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables wind_and_solar__pct: title: Wind and Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind and Solar clean__twh: @@ -204,56 +202,56 @@ tables: name: Wind and Solar bioenergy__pct: title: Bioenergy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy coal__pct: title: Coal (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal gas__pct: title: Gas (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro__pct: title: Hydro (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro nuclear__pct: title: Nuclear (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear other_fossil__pct: title: Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Fossil other_renewables__pct: title: Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Renewables solar__pct: title: Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar wind__pct: title: Wind (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind bioenergy__twh: diff --git a/etl/steps/archive/garden/ember/2023-02-20/yearly_electricity.meta.yml b/etl/steps/archive/garden/ember/2023-02-20/yearly_electricity.meta.yml index 1ac20d0c922..3229696770d 100644 --- a/etl/steps/archive/garden/ember/2023-02-20/yearly_electricity.meta.yml +++ b/etl/steps/archive/garden/ember/2023-02-20/yearly_electricity.meta.yml @@ -4,23 +4,21 @@ dataset: title: Yearly Electricity Data (Ember, 2023) short_name: yearly_electricity description: | - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on Ember's Yearly Electricity Data (2023). - published_by: Ember - publication_year: 2023 - publication_date: 2023-01-31 - date_accessed: 2023-02-20 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - + - name: Our World in Data based on Ember's Yearly Electricity Data (2023). + published_by: Ember + publication_year: 2023 + publication_date: 2023-01-31 + date_accessed: 2023-02-20 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ tables: capacity: - title: "Capacity" + title: Capacity variables: clean__gw: title: Clean (GW) @@ -113,7 +111,7 @@ tables: display: name: Wind electricity_demand: - title: "Electricity demand" + title: Electricity demand variables: demand__twh: title: Demand (TWh) @@ -132,42 +130,42 @@ tables: display: name: Demand per capita electricity_generation: - title: "Electricity generation" + title: Electricity generation variables: clean__pct: title: Clean (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Clean fossil__pct: title: Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil gas_and_other_fossil__pct: title: Gas and Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas and Other Fossil hydro__bioenergy_and_other_renewables__pct: title: Hydro, Bioenergy and Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro, Bioenergy and Other Renewables renewables__pct: title: Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables wind_and_solar__pct: title: Wind and Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind and Solar clean__twh: @@ -208,56 +206,56 @@ tables: name: Wind and Solar bioenergy__pct: title: Bioenergy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy coal__pct: title: Coal (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal gas__pct: title: Gas (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro__pct: title: Hydro (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro nuclear__pct: title: Nuclear (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear other_fossil__pct: title: Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Fossil other_renewables__pct: title: Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Renewables solar__pct: title: Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar wind__pct: title: Wind (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind bioenergy__twh: @@ -321,7 +319,7 @@ tables: display: name: Total Generation electricity_imports: - title: "Electricity imports" + title: Electricity imports variables: net_imports__twh: title: Net Imports (TWh) @@ -330,7 +328,7 @@ tables: display: name: Net Imports power_sector_emissions: - title: "Power sector emissions" + title: Power sector emissions variables: clean__mtco2: title: Clean (mtCO2) diff --git a/etl/steps/archive/garden/ember/2023-06-01/yearly_electricity.meta.yml b/etl/steps/archive/garden/ember/2023-06-01/yearly_electricity.meta.yml index 8addeefc83d..1cff8a10da4 100644 --- a/etl/steps/archive/garden/ember/2023-06-01/yearly_electricity.meta.yml +++ b/etl/steps/archive/garden/ember/2023-06-01/yearly_electricity.meta.yml @@ -1,7 +1,7 @@ dataset: title: Yearly Electricity Data (Ember, 2023b) description: | - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. @@ -102,7 +102,7 @@ tables: display: name: Wind electricity_demand: - title: "Electricity demand" + title: Electricity demand variables: demand__twh: title: Demand (TWh) @@ -121,42 +121,42 @@ tables: display: name: Demand per capita electricity_generation: - title: "Electricity generation" + title: Electricity generation variables: clean__pct: title: Clean (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Clean fossil__pct: title: Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil gas_and_other_fossil__pct: title: Gas and Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas and Other Fossil hydro__bioenergy_and_other_renewables__pct: title: Hydro, Bioenergy and Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro, Bioenergy and Other Renewables renewables__pct: title: Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables wind_and_solar__pct: title: Wind and Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind and Solar clean__twh: @@ -197,56 +197,56 @@ tables: name: Wind and Solar bioenergy__pct: title: Bioenergy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy coal__pct: title: Coal (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal gas__pct: title: Gas (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro__pct: title: Hydro (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro nuclear__pct: title: Nuclear (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear other_fossil__pct: title: Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Fossil other_renewables__pct: title: Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Renewables solar__pct: title: Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar wind__pct: title: Wind (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind bioenergy__twh: @@ -310,7 +310,7 @@ tables: display: name: Total Generation electricity_imports: - title: "Electricity imports" + title: Electricity imports variables: net_imports__twh: title: Net Imports (TWh) @@ -319,7 +319,7 @@ tables: display: name: Net Imports power_sector_emissions: - title: "Power sector emissions" + title: Power sector emissions variables: clean__mtco2: title: Clean (mtCO2) diff --git a/etl/steps/archive/garden/emissions/2023-05-03/owid_co2.meta.yml b/etl/steps/archive/garden/emissions/2023-05-03/owid_co2.meta.yml index 080d012dcff..34dd2c1b65f 100644 --- a/etl/steps/archive/garden/emissions/2023-05-03/owid_co2.meta.yml +++ b/etl/steps/archive/garden/emissions/2023-05-03/owid_co2.meta.yml @@ -3,7 +3,7 @@ dataset: description: | OWID CO2 dataset. - This dataset will be loaded by the co2-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the co2-data repository](https://github.com/owid/co2-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' original metadata. diff --git a/etl/steps/archive/garden/energy/2022-07-20/fossil_fuel_production.meta.yml b/etl/steps/archive/garden/energy/2022-07-20/fossil_fuel_production.meta.yml index 9f22a9b9c77..e552be31878 100644 --- a/etl/steps/archive/garden/energy/2022-07-20/fossil_fuel_production.meta.yml +++ b/etl/steps/archive/garden/energy/2022-07-20/fossil_fuel_production.meta.yml @@ -3,136 +3,172 @@ dataset: version: 2022-07-20 title: Fossil fuel production (BP & Shift, 2022) short_name: fossil_fuel_production - description: | - This dataset on fossil fuel production is generated by combining the latest data from the BP Statistical Review of World Energy and The Shift Dataportal. + description: >- + This dataset on fossil fuel production is generated by combining the latest data from [the BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) + and [The Shift Dataportal](https://www.theshiftdataportal.org/energy). + BP provide fossil fuel production data from 1965 onwards (and crude prices from 1861 onwards). The Shift Dataportal provides long-term data from 1900, but only extends to 2016. - To maintain consistency with the energy datasets on Our World in Data, we have taken BP data as preference – meaning if BP provides data for the given country and year, this is used. Where data is not available from BP for a given country, or pre-1965 we rely on data from Shift. + + To maintain consistency with the energy datasets on Our World in Data, we have taken BP data as preference – meaning if BP provides data for the given country and year, this is used. + Where data is not available from BP for a given country, or pre-1965 we rely on data from Shift. + We have converted primary production in exajoules to terawatt-hours using the conversion factor: 1,000,000 / 3,600 ~ 278. - Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - BP's region definitions, denoted with "(BP)", are: - * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. - * "Australasia (BP)": Australia, New Zealand. - * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. - * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. - * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama - * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. - * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. - * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. - * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. - * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. - * "North America (BP)": US (excluding US territories), Canada, Mexico - * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. - * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. - * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. - * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. - * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. - * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. - - Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe (BP)", or "Other CIS (BP)"). We define our regions in the following way: - * "Africa" - All African countries + "Other Africa (BP)". - * "Asia" - All Asian countries + "Other Middle East (BP)" + "Other CIS (BP)" + "Other Asia Pacific (BP)". - * "Europe" - All European countries + "Other Europe (BP)". - * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". - * "Oceania" - All Oceanian countries. - * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. - - - name: Our World in Data based on The Shift Dataportal (2022) - published_by: The Shift Dataportal - date_accessed: 2022-07-18 - url: https://www.theshiftdataportal.org/energy + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + description: >- + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America + includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions + like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These + aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + + + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), + denoted with "(BP)", are: + + * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, + Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. + + * "Australasia (BP)": Australia, New Zealand. + + * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. + + * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. + + * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama + + * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. + + * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. + + * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. + + * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. + + * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. + + * "North America (BP)": US (excluding US territories), Canada, Mexico + + * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. + + * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, + Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. + + * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. + + * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. + + * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. + + * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. + + + Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe (BP)", or "Other CIS (BP)"). We define our regions in the following way: + + * "Africa" - All African countries + "Other Africa (BP)". + + * "Asia" - All Asian countries + "Other Middle East (BP)" + "Other CIS (BP)" + "Other Asia Pacific (BP)". + + * "Europe" - All European countries + "Other Europe (BP)". + + * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". + + * "Oceania" - All Oceanian countries. + + * "South America" - All South American countries + "Other South America (BP)". + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included + (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions + [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). + - name: Our World in Data based on The Shift Dataportal (2022) + published_by: The Shift Dataportal + date_accessed: 2022-07-18 + url: https://www.theshiftdataportal.org/energy tables: fossil_fuel_production: variables: annual_change_in_coal_production__pct: - title: "Annual change in coal production (%)" - short_unit: "%" - unit: "%" + title: Annual change in coal production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_coal_production__twh: - title: "Annual change in coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_gas_production__pct: - title: "Annual change in gas production (%)" - short_unit: "%" - unit: "%" + title: Annual change in gas production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_gas_production__twh: - title: "Annual change in gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_oil_production__pct: - title: "Annual change in oil production (%)" - short_unit: "%" - unit: "%" + title: Annual change in oil production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in oil production" + name: Annual change in oil production annual_change_in_oil_production__twh: - title: "Annual change in oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in oil production" + name: Annual change in oil production coal_production__twh: - title: "Coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Coal production" + name: Coal production numDecimalPlaces: 0 coal_production_per_capita__kwh: - title: "Coal production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Coal production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Coal production per capita" + name: Coal production per capita numDecimalPlaces: 0 gas_production__twh: - title: "Gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Gas production" + name: Gas production numDecimalPlaces: 0 gas_production_per_capita__kwh: - title: "Gas production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Gas production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Gas production per capita" + name: Gas production per capita numDecimalPlaces: 0 oil_production__twh: - title: "Oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Oil production" + name: Oil production numDecimalPlaces: 0 oil_production_per_capita__kwh: - title: "Oil production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Oil production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Oil production per capita" + name: Oil production per capita numDecimalPlaces: 0 diff --git a/etl/steps/archive/garden/energy/2022-07-29/primary_energy_consumption.meta.yml b/etl/steps/archive/garden/energy/2022-07-29/primary_energy_consumption.meta.yml index 03bd51a31c3..cdee70489d7 100644 --- a/etl/steps/archive/garden/energy/2022-07-29/primary_energy_consumption.meta.yml +++ b/etl/steps/archive/garden/energy/2022-07-29/primary_energy_consumption.meta.yml @@ -3,75 +3,117 @@ dataset: version: 2022-07-29 title: Primary energy consumption (BP & EIA, 2022) short_name: primary_energy_consumption - description: | + description: >- Primary energy consumption data was compiled by Our World in Data based on two key data sources: - 1. BP Statistical Review of World Energy. - 2. International energy data from the U.S. Energy Information Administration (EIA). - BP provides the longest and most up-to-date time-series of primary energy. However, it does not provide data for all countries. We have therefore supplemented this dataset with energy data from the EIA. Where BP provides data for a given country, this data is adopted; for countries where this data is missing, we rely on EIA energy figures. + 1. [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + 2. [International energy data from the U.S. Energy Information Administration (EIA)](https://www.eia.gov/international/data/world/total-energy/more-total-energy-data). + + + BP provides the longest and most up-to-date time-series of primary energy. However, it does not provide data for all countries. We have therefore supplemented this dataset + with energy data from the EIA. Where BP provides data for a given country, this data is adopted; for countries where this data is missing, we rely on EIA energy figures. + + + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). + + + To calculate energy per unit of GDP, we use total real GDP figures from [the Maddison Project Database, version 2020](https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020). - To calculate energy per unit of GDP, we use total real GDP figures from the Maddison Project Database, version 2020. This dataset is based on Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update ”. GDP is measured in 2011$ which are PPP-adjusted. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - BP's region definitions, denoted with "(BP)", are: - * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. - * "Australasia (BP)": Australia, New Zealand. - * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. - * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. - * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama - * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. - * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. - * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. - * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. - * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. - * "North America (BP)": US (excluding US territories), Canada, Mexico - * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. - * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. - * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. - * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. - * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. - * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. - - Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe (BP)", or "Other CIS (BP)"). We define our regions in the following way: - * "Africa" - All African countries + "Other Africa (BP)". - * "Asia" - All Asian countries + "Other Middle East (BP)" + "Other CIS (BP)" + "Other Asia Pacific (BP)". - * "Europe" - All European countries + "Other Europe (BP)". - * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". - * "Oceania" - All Oceanian countries. - * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. - - - name: Our World in Data based on EIA International energy data (2022) - published_by: U.S. Energy Information Administration (EIA) - date_accessed: 2022-07-27 - url: https://www.eia.gov/opendata/bulkfiles.php - description: | - Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their Bulk Download Facility. - - EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with our region definitions). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - - name: Maddison Project Database 2020 (Bolt and van Zanden, 2020) - published_by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update“. - date_accessed: 2022-04-12 - url: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + description: >- + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, + whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). + For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data + aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + + + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), + denoted with "(BP)", are: + + * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, + Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, + Papua New Guinea and Oceania. + + * "Australasia (BP)": Australia, New Zealand. + + * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. + + * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. + + * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama + + * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. + + * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. + + * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. + + * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. + + * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. + + * "North America (BP)": US (excluding US territories), Canada, Mexico + + * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. + + * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, + Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, + Japan, Mexico, New Zealand, South Korea, US. + + * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. + + * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. + + * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. + + * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. + + + Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe (BP)", or "Other CIS (BP)"). We define our regions in the following way: + + * "Africa" - All African countries + "Other Africa (BP)". + + * "Asia" - All Asian countries + "Other Middle East (BP)" + "Other CIS (BP)" + "Other Asia Pacific (BP)". + + * "Europe" - All European countries + "Other Europe (BP)". + + * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". + + * "Oceania" - All Oceanian countries. + + * "South America" - All South American countries + "Other South America (BP)". + + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). + Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included + in "Other Africa (BP)"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). + - name: Our World in Data based on EIA International energy data (2022) + published_by: U.S. Energy Information Administration (EIA) + date_accessed: 2022-07-27 + url: https://www.eia.gov/opendata/bulkfiles.php + description: | + Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their [Bulk Download Facility](https://www.eia.gov/opendata/bulkfiles.php). + EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with + [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data + using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the + contributions from the countries in the region. + - name: Maddison Project Database 2020 (Bolt and van Zanden, 2020) + published_by: "Bolt, Jutta and Jan Luiten van Zanden (2020), 'Maddison style estimates of the evolution of the world economy. A new 2020 update'." + date_accessed: 2022-04-12 + url: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 tables: primary_energy_consumption: variables: annual_change_in_primary_energy_consumption__pct: title: Annual change in primary energy consumption (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Annual change in primary energy consumption annual_change_in_primary_energy_consumption__twh: @@ -84,7 +126,9 @@ tables: title: GDP short_unit: $ unit: 2011 int-$ - description: Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over + time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. display: numDecimalPlaces: 0 population: diff --git a/etl/steps/archive/garden/energy/2022-12-13/electricity_mix.meta.yml b/etl/steps/archive/garden/energy/2022-12-13/electricity_mix.meta.yml index 8cad213e6bc..1d5e478c1b7 100644 --- a/etl/steps/archive/garden/energy/2022-12-13/electricity_mix.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-13/electricity_mix.meta.yml @@ -5,9 +5,9 @@ dataset: short_name: electricity_mix description: | Data is compiled by Our World in Data based on three main sources: - - BP Statistical Review of World Energy. - - Ember Yearly Electricity Data (2022). - - Ember European Electricity Review (2022). + - [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + - [Ember Yearly Electricity Data (2022)](https://ember-climate.org/data-catalogue/yearly-electricity-data/). + - [Ember European Electricity Review (2022)](https://ember-climate.org/insights/research/european-electricity-review-2022/). Ember compile their global dataset from various sources including: - Eurostat: Annual European generation and import data, and monthly data in some cases where better sources are not available. @@ -18,16 +18,16 @@ dataset: - IRENA: Annual global capacity data for all non-fossil fuel types, and for Other Fossil where available. - WRI: Annual global capacity data for Other Fossil where other sources are not available. - European carbon intensities rely on data from the European Environment Agency (EEA). - - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found here. - - A complete list of data sources for each individual country in Ember's European Electricity Review can be found here. + - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found [here](https://ember-climate.org/app/uploads/2022/07/Ember-Electricity-Data-Methodology.pdf). + - A complete list of data sources for each individual country in Ember's European Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/02/EER-Methodology.pdf). We rely on Ember as the primary source of electricity consumption data. While BP provides primary energy (not just electricity) consumption data and it provides a longer time-series (dating back to 1965) than Ember (which only dates back to 1990), BP does not provide data for all countries or for all sources of electricity (for example, only Ember provides data on electricity from bioenergy). So, where data from Ember is available for a given country and year, we rely on it as the primary source. We then supplement this with data from BP where data from Ember is not available. Our World in Data has converted absolute electricity production by source to the share in the mix by dividing each by total electricity production. - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -53,33 +53,29 @@ dataset: * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "Middle East (Ember)": Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates and Yemen. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Our World in Data based on Ember's Yearly Electricity Data (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-12-13 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Our World in Data based on Ember's European Electricity Review (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Our World in Data based on Ember's Yearly Electricity Data (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-12-13 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Our World in Data based on Ember's European Electricity Review (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: electricity_mix: variables: @@ -91,8 +87,8 @@ tables: name: Bioenergy bioenergy_share_of_electricity__pct: title: Bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy co2_intensity__gco2_kwh: @@ -109,8 +105,8 @@ tables: name: Coal coal_share_of_electricity__pct: title: Coal (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal fossil_generation__twh: @@ -121,8 +117,8 @@ tables: name: Fossil fuels fossil_share_of_electricity__pct: title: Fossil fuels (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil fuels gas_generation__twh: @@ -133,8 +129,8 @@ tables: name: Gas gas_share_of_electricity__pct: title: Gas (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro_generation__twh: @@ -145,8 +141,8 @@ tables: name: Hydropower hydro_share_of_electricity__pct: title: Hydro (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydropower low_carbon_generation__twh: @@ -157,14 +153,14 @@ tables: name: Low-carbon electricity low_carbon_share_of_electricity__pct: title: Low-carbon electricity (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Share of electricity from low-carbon sources net_imports_share_of_demand__pct: title: Net electricity imports as a share of demand (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Net electricity imports as a share of demand nuclear_generation__twh: @@ -175,8 +171,8 @@ tables: name: Nuclear nuclear_share_of_electricity__pct: title: Nuclear (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear oil_generation__twh: @@ -187,8 +183,8 @@ tables: name: Oil oil_share_of_electricity__pct: title: Oil (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Oil other_renewables_excluding_bioenergy_generation__twh: @@ -199,8 +195,8 @@ tables: name: Other renewables, excluding bioenergy other_renewables_excluding_bioenergy_share_of_electricity__pct: title: Other renewables excluding bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, excluding bioenergy other_renewables_including_bioenergy_generation__twh: @@ -211,8 +207,8 @@ tables: name: Other renewables, including bioenergy other_renewables_including_bioenergy_share_of_electricity__pct: title: Other renewables including bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, including bioenergy per_capita_bioenergy_generation__kwh: @@ -333,8 +329,8 @@ tables: name: Renewables renewable_share_of_electricity__pct: title: Renewables (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables numDecimalPlaces: 2 @@ -346,8 +342,8 @@ tables: name: Solar solar_share_of_electricity__pct: title: Solar (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar total_demand__twh: @@ -358,8 +354,8 @@ tables: name: Electricity demand total_electricity_share_of_primary_energy__pct: title: Electricity as share of primary energy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Electricity as share of primary energy total_emissions__mtco2: @@ -388,7 +384,7 @@ tables: name: Wind wind_share_of_electricity__pct: title: Wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind diff --git a/etl/steps/archive/garden/energy/2022-12-13/owid_energy.meta.yml b/etl/steps/archive/garden/energy/2022-12-13/owid_energy.meta.yml index 74e313af5b4..71459dcc410 100644 --- a/etl/steps/archive/garden/energy/2022-12-13/owid_energy.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-13/owid_energy.meta.yml @@ -6,7 +6,7 @@ dataset: description: | OWID Energy dataset. - This dataset will be loaded by the energy-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the energy-data repository](https://github.com/owid/energy-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' metadata and the content of owid_energy_variable_mapping.csv. diff --git a/etl/steps/archive/garden/energy/2022-12-13/uk_historical_electricity.meta.yml b/etl/steps/archive/garden/energy/2022-12-13/uk_historical_electricity.meta.yml index 2a846181815..a864510d549 100644 --- a/etl/steps/archive/garden/energy/2022-12-13/uk_historical_electricity.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-13/uk_historical_electricity.meta.yml @@ -4,33 +4,28 @@ dataset: title: UK historical electricity (DUKES, 2022b) short_name: uk_historical_electricity description: | - All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy. + All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from [the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy](https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes). - All other data is sourced from the BP's Statistical Review of World Energy and Ember's Yearly Electricity Data. Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. + All other data is sourced from the [BP's Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [Ember's Yearly Electricity Data](https://ember-climate.org/data-catalogue/yearly-electricity-data/). Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. sources: - - - name: Digest of UK Energy Statistics - published_by: UK's Department for Business, Energy & Industrial Strategy - date_accessed: 2022-09-21 - url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data - - - name: BP Statistical Review of World Energy - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Ember's Yearly Electricity Data - published_by: Ember - publication_year: 2022 - date_accessed: 2022-12-13 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Ember's European Electricity Review - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Digest of UK Energy Statistics + published_by: UK's Department for Business, Energy & Industrial Strategy + date_accessed: 2022-09-21 + url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data + - name: BP Statistical Review of World Energy + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Ember's Yearly Electricity Data + published_by: Ember + publication_year: 2022 + date_accessed: 2022-12-13 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Ember's European Electricity Review + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: uk_historical_electricity: variables: diff --git a/etl/steps/archive/garden/energy/2022-12-28/electricity_mix.meta.yml b/etl/steps/archive/garden/energy/2022-12-28/electricity_mix.meta.yml index 7717edf5a75..84faa0b650e 100644 --- a/etl/steps/archive/garden/energy/2022-12-28/electricity_mix.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-28/electricity_mix.meta.yml @@ -5,9 +5,9 @@ dataset: short_name: electricity_mix description: | Data is compiled by Our World in Data based on three main sources: - - BP Statistical Review of World Energy. - - Ember Yearly Electricity Data (2022). - - Ember European Electricity Review (2022). + - [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + - [Ember Yearly Electricity Data (2022)](https://ember-climate.org/data-catalogue/yearly-electricity-data/). + - [Ember European Electricity Review (2022)](https://ember-climate.org/insights/research/european-electricity-review-2022/). Ember compile their global dataset from various sources including: - Eurostat: Annual European generation and import data, and monthly data in some cases where better sources are not available. @@ -18,16 +18,16 @@ dataset: - IRENA: Annual global capacity data for all non-fossil fuel types, and for Other Fossil where available. - WRI: Annual global capacity data for Other Fossil where other sources are not available. - European carbon intensities rely on data from the European Environment Agency (EEA). - - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found here. - - A complete list of data sources for each individual country in Ember's European Electricity Review can be found here. + - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found [here](https://ember-climate.org/app/uploads/2022/07/Ember-Electricity-Data-Methodology.pdf). + - A complete list of data sources for each individual country in Ember's European Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/02/EER-Methodology.pdf). We rely on Ember as the primary source of electricity consumption data. While BP provides primary energy (not just electricity) consumption data and it provides a longer time-series (dating back to 1965) than Ember (which only dates back to 1990), BP does not provide data for all countries or for all sources of electricity (for example, only Ember provides data on electricity from bioenergy). So, where data from Ember is available for a given country and year, we rely on it as the primary source. We then supplement this with data from BP where data from Ember is not available. Our World in Data has converted absolute electricity production by source to the share in the mix by dividing each by total electricity production. - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -53,33 +53,29 @@ dataset: * "North America" - All North American countries + "Other Caribbean" + "Other North America". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "Middle East (Ember)": Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates and Yemen. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Our World in Data based on Ember's Yearly Electricity Data (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-12-13 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Our World in Data based on Ember's European Electricity Review (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Our World in Data based on Ember's Yearly Electricity Data (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-12-13 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Our World in Data based on Ember's European Electricity Review (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: electricity_mix: variables: @@ -91,8 +87,8 @@ tables: name: Bioenergy bioenergy_share_of_electricity__pct: title: Bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy co2_intensity__gco2_kwh: @@ -109,8 +105,8 @@ tables: name: Coal coal_share_of_electricity__pct: title: Coal (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal fossil_generation__twh: @@ -121,8 +117,8 @@ tables: name: Fossil fuels fossil_share_of_electricity__pct: title: Fossil fuels (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil fuels gas_generation__twh: @@ -133,8 +129,8 @@ tables: name: Gas gas_share_of_electricity__pct: title: Gas (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro_generation__twh: @@ -145,8 +141,8 @@ tables: name: Hydropower hydro_share_of_electricity__pct: title: Hydro (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydropower low_carbon_generation__twh: @@ -157,14 +153,14 @@ tables: name: Low-carbon electricity low_carbon_share_of_electricity__pct: title: Low-carbon electricity (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Share of electricity from low-carbon sources net_imports_share_of_demand__pct: title: Net electricity imports as a share of demand (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Net electricity imports as a share of demand nuclear_generation__twh: @@ -175,8 +171,8 @@ tables: name: Nuclear nuclear_share_of_electricity__pct: title: Nuclear (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear oil_generation__twh: @@ -187,8 +183,8 @@ tables: name: Oil oil_share_of_electricity__pct: title: Oil (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Oil other_renewables_excluding_bioenergy_generation__twh: @@ -199,8 +195,8 @@ tables: name: Other renewables, excluding bioenergy other_renewables_excluding_bioenergy_share_of_electricity__pct: title: Other renewables excluding bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, excluding bioenergy other_renewables_including_bioenergy_generation__twh: @@ -211,8 +207,8 @@ tables: name: Other renewables, including bioenergy other_renewables_including_bioenergy_share_of_electricity__pct: title: Other renewables including bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, including bioenergy per_capita_bioenergy_generation__kwh: @@ -333,8 +329,8 @@ tables: name: Renewables renewable_share_of_electricity__pct: title: Renewables (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables numDecimalPlaces: 2 @@ -346,8 +342,8 @@ tables: name: Solar solar_share_of_electricity__pct: title: Solar (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar total_demand__twh: @@ -358,8 +354,8 @@ tables: name: Electricity demand total_electricity_share_of_primary_energy__pct: title: Electricity as share of primary energy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Electricity as share of primary energy total_emissions__mtco2: @@ -388,7 +384,7 @@ tables: name: Wind wind_share_of_electricity__pct: title: Wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind diff --git a/etl/steps/archive/garden/energy/2022-12-28/fossil_fuel_production.meta.yml b/etl/steps/archive/garden/energy/2022-12-28/fossil_fuel_production.meta.yml index f7e0eb61cda..ae2b1aab34e 100644 --- a/etl/steps/archive/garden/energy/2022-12-28/fossil_fuel_production.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-28/fossil_fuel_production.meta.yml @@ -3,136 +3,167 @@ dataset: version: 2022-12-28 title: Fossil fuel production (BP & Shift, 2022b) short_name: fossil_fuel_production - description: | - This dataset on fossil fuel production is generated by combining the latest data from the BP Statistical Review of World Energy and The Shift Dataportal. + description: >- + This dataset on fossil fuel production is generated by combining the latest data from [the BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) + and [The Shift Dataportal](https://www.theshiftdataportal.org/energy). BP provide fossil fuel production data from 1965 onwards (and crude prices from 1861 onwards). The Shift Dataportal provides long-term data from 1900, but only extends to 2016. - To maintain consistency with the energy datasets on Our World in Data, we have taken BP data as preference - meaning if BP provides data for the given country and year, this is used. Where data is not available from BP for a given country, or pre-1965 we rely on data from Shift. + To maintain consistency with the energy datasets on Our World in Data, we have taken BP data as preference - meaning if BP provides data for the given country and year, this is used. Where data is not available + from BP for a given country, or pre-1965 we rely on data from Shift. We have converted primary production in exajoules to terawatt-hours using the conversion factor: 1,000,000 / 3,600 ~ 278. - Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - BP's region definitions, denoted with "(BP)", are: - * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. - * "Australasia (BP)": Australia, New Zealand. - * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. - * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. - * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama - * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. - * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. - * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. - * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. - * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. - * "North America (BP)": US (excluding US territories), Canada, Mexico - * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. - * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. - * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. - * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. - * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. - * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. - - Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: - * "Africa" - All African countries + "Other Africa". - * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". - * "Europe" - All European countries + "Other Europe". - * "North America" - All North American countries + "Other Caribbean" + "Other North America". - * "Oceania" - All Oceanian countries. - * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. - - - name: Our World in Data based on The Shift Dataportal (2022) - published_by: The Shift Dataportal - date_accessed: 2022-07-18 - url: https://www.theshiftdataportal.org/energy + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + description: >- + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes + countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like + "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These + aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), + denoted with "(BP)", are: + + * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. + + * "Australasia (BP)": Australia, New Zealand. + + * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. + + * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. + + * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama + + * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. + + * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. + + * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. + + * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. + + * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. + + * "North America (BP)": US (excluding US territories), Canada, Mexico + + * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. + + * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. + + * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. + + * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. + + * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. + + * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. + + + Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: + + * "Africa" - All African countries + "Other Africa". + + * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". + + * "Europe" - All European countries + "Other Europe". + + * "North America" - All North American countries + "Other Caribbean" + "Other North America". + + * "Oceania" - All Oceanian countries. + + * "South America" - All South American countries + "Other South America". + + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). + Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). + Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). + - name: Our World in Data based on The Shift Dataportal (2022) + published_by: The Shift Dataportal + date_accessed: 2022-07-18 + url: https://www.theshiftdataportal.org/energy tables: fossil_fuel_production: variables: annual_change_in_coal_production__pct: - title: "Annual change in coal production (%)" - short_unit: "%" - unit: "%" + title: Annual change in coal production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_coal_production__twh: - title: "Annual change in coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_gas_production__pct: - title: "Annual change in gas production (%)" - short_unit: "%" - unit: "%" + title: Annual change in gas production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_gas_production__twh: - title: "Annual change in gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_oil_production__pct: - title: "Annual change in oil production (%)" - short_unit: "%" - unit: "%" + title: Annual change in oil production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in oil production" + name: Annual change in oil production annual_change_in_oil_production__twh: - title: "Annual change in oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in oil production" + name: Annual change in oil production coal_production__twh: - title: "Coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Coal production" + name: Coal production numDecimalPlaces: 0 coal_production_per_capita__kwh: - title: "Coal production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Coal production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Coal production per capita" + name: Coal production per capita numDecimalPlaces: 0 gas_production__twh: - title: "Gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Gas production" + name: Gas production numDecimalPlaces: 0 gas_production_per_capita__kwh: - title: "Gas production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Gas production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Gas production per capita" + name: Gas production per capita numDecimalPlaces: 0 oil_production__twh: - title: "Oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Oil production" + name: Oil production numDecimalPlaces: 0 oil_production_per_capita__kwh: - title: "Oil production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Oil production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Oil production per capita" + name: Oil production per capita numDecimalPlaces: 0 diff --git a/etl/steps/archive/garden/energy/2022-12-28/owid_energy.meta.yml b/etl/steps/archive/garden/energy/2022-12-28/owid_energy.meta.yml index 7e57fdc9f3d..aae6ccecf70 100644 --- a/etl/steps/archive/garden/energy/2022-12-28/owid_energy.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-28/owid_energy.meta.yml @@ -6,7 +6,7 @@ dataset: description: | OWID Energy dataset. - This dataset will be loaded by the energy-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the energy-data repository](https://github.com/owid/energy-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' metadata and the content of owid_energy_variable_mapping.csv. diff --git a/etl/steps/archive/garden/energy/2022-12-28/primary_energy_consumption.meta.yml b/etl/steps/archive/garden/energy/2022-12-28/primary_energy_consumption.meta.yml index a192a847059..ccc4663fda6 100644 --- a/etl/steps/archive/garden/energy/2022-12-28/primary_energy_consumption.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-28/primary_energy_consumption.meta.yml @@ -3,75 +3,107 @@ dataset: version: 2022-12-28 title: Primary energy consumption (BP & EIA, 2022) short_name: primary_energy_consumption - description: | + description: >- Primary energy consumption data was compiled by Our World in Data based on two key data sources: - 1. BP Statistical Review of World Energy. - 2. International energy data from the U.S. Energy Information Administration (EIA). - BP provides the longest and most up-to-date time-series of primary energy. However, it does not provide data for all countries. We have therefore supplemented this dataset with energy data from the EIA. Where BP provides data for a given country, this data is adopted; for countries where this data is missing, we rely on EIA energy figures. + 1. [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + 2. [International energy data from the U.S. Energy Information Administration (EIA)](https://www.eia.gov/international/data/world/total-energy/more-total-energy-data). - To calculate energy per unit of GDP, we use total real GDP figures from the Maddison Project Database, version 2020. + + BP provides the longest and most up-to-date time-series of primary energy. However, it does not provide data for all countries. We have therefore supplemented this dataset with energy data + from the EIA. Where BP provides data for a given country, this data is adopted; for countries where this data is missing, we rely on EIA energy figures. + + + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). + + + To calculate energy per unit of GDP, we use total real GDP figures from [the Maddison Project Database, version 2020](https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020). This dataset is based on Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update ”. GDP is measured in 2011$ which are PPP-adjusted. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - BP's region definitions, denoted with "(BP)", are: - * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. - * "Australasia (BP)": Australia, New Zealand. - * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. - * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. - * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama - * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. - * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. - * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. - * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. - * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. - * "North America (BP)": US (excluding US territories), Canada, Mexico - * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. - * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. - * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. - * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. - * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. - * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. - - Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: - * "Africa" - All African countries + "Other Africa". - * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". - * "Europe" - All European countries + "Other Europe". - * "North America" - All North American countries + "Other Caribbean" + "Other North America". - * "Oceania" - All Oceanian countries. - * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. - - - name: Our World in Data based on EIA International energy data (2022) - published_by: U.S. Energy Information Administration (EIA) - date_accessed: 2022-07-27 - url: https://www.eia.gov/opendata/bulkfiles.php - description: | - Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their Bulk Download Facility. - - EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with our region definitions). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - - name: Maddison Project Database 2020 (Bolt and van Zanden, 2020) - published_by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update“. - date_accessed: 2022-04-12 - url: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + description: >- + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + + + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: + + * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, + Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. + + * "Australasia (BP)": Australia, New Zealand. + + * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. + + * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. + + * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama + + * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. + + * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. + + * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. + + * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. + + * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. + + * "North America (BP)": US (excluding US territories), Canada, Mexico + + * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. + + * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, + Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. + + * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. + + * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. + + * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. + + * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. + + + Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: + + * "Africa" - All African countries + "Other Africa". + + * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". + + * "Europe" - All European countries + "Other Europe". + + * "North America" - All North American countries + "Other Caribbean" + "Other North America". + + * "Oceania" - All Oceanian countries. + + * "South America" - All South American countries + "Other South America". + + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to + other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions + [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). + - name: Our World in Data based on EIA International energy data (2022) + published_by: U.S. Energy Information Administration (EIA) + date_accessed: 2022-07-27 + url: https://www.eia.gov/opendata/bulkfiles.php + description: | + Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their [Bulk Download Facility](https://www.eia.gov/opendata/bulkfiles.php). + EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + - name: Maddison Project Database 2020 (Bolt and van Zanden, 2020) + published_by: "Bolt, Jutta and Jan Luiten van Zanden (2020), 'Maddison style estimates of the evolution of the world economy. A new 2020 update'." + date_accessed: 2022-04-12 + url: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 tables: primary_energy_consumption: variables: annual_change_in_primary_energy_consumption__pct: title: Annual change in primary energy consumption (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Annual change in primary energy consumption annual_change_in_primary_energy_consumption__twh: @@ -84,7 +116,9 @@ tables: title: GDP short_unit: $ unit: 2011 int-$ - description: Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over + time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. display: numDecimalPlaces: 0 population: diff --git a/etl/steps/archive/garden/energy/2022-12-28/uk_historical_electricity.meta.yml b/etl/steps/archive/garden/energy/2022-12-28/uk_historical_electricity.meta.yml index 81510523a6e..fc14f13a220 100644 --- a/etl/steps/archive/garden/energy/2022-12-28/uk_historical_electricity.meta.yml +++ b/etl/steps/archive/garden/energy/2022-12-28/uk_historical_electricity.meta.yml @@ -4,33 +4,28 @@ dataset: title: UK historical electricity (DUKES, 2022c) short_name: uk_historical_electricity description: | - All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy. + All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from [the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy](https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes). - All other data is sourced from the BP's Statistical Review of World Energy and Ember's Yearly Electricity Data. Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. + All other data is sourced from the [BP's Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [Ember's Yearly Electricity Data](https://ember-climate.org/data-catalogue/yearly-electricity-data/). Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. sources: - - - name: Digest of UK Energy Statistics - published_by: UK's Department for Business, Energy & Industrial Strategy - date_accessed: 2022-09-21 - url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data - - - name: BP Statistical Review of World Energy - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Ember's Yearly Electricity Data - published_by: Ember - publication_year: 2022 - date_accessed: 2022-12-13 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Ember's European Electricity Review - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Digest of UK Energy Statistics + published_by: UK's Department for Business, Energy & Industrial Strategy + date_accessed: 2022-09-21 + url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data + - name: BP Statistical Review of World Energy + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Ember's Yearly Electricity Data + published_by: Ember + publication_year: 2022 + date_accessed: 2022-12-13 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Ember's European Electricity Review + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: uk_historical_electricity: variables: diff --git a/etl/steps/archive/garden/energy/2023-01-04/photovoltaic_cost_and_capacity.meta.yml b/etl/steps/archive/garden/energy/2023-01-04/photovoltaic_cost_and_capacity.meta.yml index 7da43f4504d..2b1a86bc023 100644 --- a/etl/steps/archive/garden/energy/2023-01-04/photovoltaic_cost_and_capacity.meta.yml +++ b/etl/steps/archive/garden/energy/2023-01-04/photovoltaic_cost_and_capacity.meta.yml @@ -1,48 +1,47 @@ all_sources: - - nemet_2009: &source-nemet_2009 - name: G. G. Nemet (2009) - published_by: | - Interim monitoring of cost dynamics for publicly supported energy technologies. Energy Policy 37(3): 825-835. by Nemet, G. F. (2009). - url: https://www.sciencedirect.com/science/article/abs/pii/S0301421508005910 - date_accessed: '2023-01-04' - publication_date: '2009-03-01' - publication_year: 2009 - description: | - Photovoltaic cost and capacity data between 1975 and 2003 has been taken from Nemet (2009). +- nemet_2009: &source-nemet_2009 + name: G. G. Nemet (2009) + published_by: | + Interim monitoring of cost dynamics for publicly supported energy technologies. Energy Policy 37(3): 825-835. by Nemet, G. F. (2009). + url: https://www.sciencedirect.com/science/article/abs/pii/S0301421508005910 + date_accessed: '2023-01-04' + publication_date: '2009-03-01' + publication_year: 2009 + description: | + Photovoltaic cost and capacity data between 1975 and 2003 has been taken from Nemet (2009). - Prices from Nemet (2009) have been converted to 2021 US$ using the US GDP deflator: https://www.multpl.com/gdp-deflator/table/by-year - - farmer_lafond_2016: &source-farmer_lafond_2016 - name: J. D. Farmer & F. Lafond (2016) - published_by: | - How predictable is technological progress? J. D. Farmer & F. Lafond, Research Policy Volume 45, Issue 3, April 2016, Pages 647-665. - url: https://www.sciencedirect.com/science/article/pii/S0048733315001699 - date_accessed: '2023-01-04' - publication_date: '2016-04-01' - publication_year: 2016 - description: | - Photovoltaic cost data between 2004 and 2009 has been taken from Farmer & Lafond (2016). + Prices from Nemet (2009) have been converted to 2021 US$ using the US GDP deflator: https://www.multpl.com/gdp-deflator/table/by-year +- farmer_lafond_2016: &source-farmer_lafond_2016 + name: J. D. Farmer & F. Lafond (2016) + published_by: | + How predictable is technological progress? J. D. Farmer & F. Lafond, Research Policy Volume 45, Issue 3, April 2016, Pages 647-665. + url: https://www.sciencedirect.com/science/article/pii/S0048733315001699 + date_accessed: '2023-01-04' + publication_date: '2016-04-01' + publication_year: 2016 + description: | + Photovoltaic cost data between 2004 and 2009 has been taken from Farmer & Lafond (2016). - According to Farmer & Lafond (2016), the data are mostly taken from the Santa-Fe Performance Curve Database. The database has been constructed from personal communications and from Colpier and Cornland (2002), Goldemberg et al. (2004), Lieberman (1984), Lipman and Sperling (1999), Zhao (1999), McDonald and Schrattenholzer (2001), Neij et al. (2003), Moore (2006), Nemet (2006), Schilling and Esmundo (2009). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from Koomey and Hultman (2007) and Cooper (2009). The DNA sequencing data is from Wetterstrand (2015) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. - - Prices from Farmer & Lafond (2016) have been converted to 2021 US$ using the US GDP deflator: https://www.multpl.com/gdp-deflator/table/by-year - - irena_capacity: &source-irena_capacity - name: International Renewable Energy Agency (IRENA) - published_by: © 2022 by International Renewable Energy Agency (IRENA) - url: https://www.irena.org/Statistics/Download-query-tools - date_accessed: '2022-10-20' - publication_date: '2022-07-01' - publication_year: 2022 - description: | - Photovoltaic capacity data between 2004 and 2021 has been taken from IRENA. - - irena_costs: &source-irena_costs - name: International Renewable Energy Agency (IRENA) - published_by: International Renewable Energy Agency (IRENA) © 2022 by IRENA - url: https://irena.org/publications/2022/Jul/Renewable-Power-Generation-Costs-in-2021 - date_accessed: '2022-10-20' - publication_year: 2022 - description: | - Photovoltaic cost data between 2010 and 2021 has been taken from IRENA. + According to Farmer & Lafond (2016), the data are mostly taken from the Santa-Fe [Performance Curve Database](https://pcdb.santafe.edu/). The database has been constructed from personal communications and from [Colpier and Cornland (2002)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0095), [Goldemberg et al. (2004)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0130), [Lieberman (1984)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0180), [Lipman and Sperling (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0190), [Zhao (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0310), [McDonald and Schrattenholzer (2001)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0205), [Neij et al. (2003)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0235), [Moore (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0215), [Nemet (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0240), [Schilling and Esmundo (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0265). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from [Koomey and Hultman (2007)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0165) and [Cooper (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0100). The DNA sequencing data is from [Wetterstrand (2015)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0290) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. + Prices from Farmer & Lafond (2016) have been converted to 2021 US$ using the US GDP deflator: https://www.multpl.com/gdp-deflator/table/by-year +- irena_capacity: &source-irena_capacity + name: International Renewable Energy Agency (IRENA) + published_by: "© 2022 by International Renewable Energy Agency (IRENA)" + url: https://www.irena.org/Statistics/Download-query-tools + date_accessed: '2022-10-20' + publication_date: '2022-07-01' + publication_year: 2022 + description: | + Photovoltaic capacity data between 2004 and 2021 has been taken from IRENA. +- irena_costs: &source-irena_costs + name: International Renewable Energy Agency (IRENA) + published_by: "International Renewable Energy Agency (IRENA) \xA9 2022 by IRENA" + url: https://irena.org/publications/2022/Jul/Renewable-Power-Generation-Costs-in-2021 + date_accessed: '2022-10-20' + publication_year: 2022 + description: | + Photovoltaic cost data between 2010 and 2021 has been taken from IRENA. dataset: namespace: energy short_name: photovoltaic_cost_and_capacity @@ -52,26 +51,26 @@ dataset: converted to 2021 US$ using the US GDP deflator: https://www.multpl.com/gdp-deflator/table/by-year version: '2023-01-04' sources: - - *source-nemet_2009 - - *source-farmer_lafond_2016 - - *source-irena_capacity - - *source-irena_costs + - *source-nemet_2009 + - *source-farmer_lafond_2016 + - *source-irena_capacity + - *source-irena_costs tables: photovoltaic_cost_and_capacity: variables: cost: title: Solar photovoltaic module price - short_unit: '$/W' - unit: '2021 US$ per Watt' + short_unit: $/W + unit: 2021 US$ per Watt description: | Global average price of solar photovoltaic modules. IRENA presents solar PV module price series for a number of different module technologies. Here we have adopted the series for thin film a-Si/u-Si or Global Index (from Q4 2013). sources: - - *source-nemet_2009 - - *source-farmer_lafond_2016 - - *source-irena_costs + - *source-nemet_2009 + - *source-farmer_lafond_2016 + - *source-irena_costs cost_source: title: Data source for cost data unit: '' @@ -80,11 +79,11 @@ tables: title: Solar photovoltaic cumulative capacity description: | Global cumulative capacity of solar photovoltaics. - short_unit: 'MW' - unit: 'megawatts' + short_unit: MW + unit: megawatts sources: - - *source-nemet_2009 - - *source-irena_capacity + - *source-nemet_2009 + - *source-irena_capacity cumulative_capacity_source: title: Data source for cumulative capacity data unit: '' diff --git a/etl/steps/archive/garden/energy/2023-02-20/electricity_mix.meta.yml b/etl/steps/archive/garden/energy/2023-02-20/electricity_mix.meta.yml index 30d2ec07878..6f87b79675d 100644 --- a/etl/steps/archive/garden/energy/2023-02-20/electricity_mix.meta.yml +++ b/etl/steps/archive/garden/energy/2023-02-20/electricity_mix.meta.yml @@ -5,9 +5,9 @@ dataset: short_name: electricity_mix description: | Data is compiled by Our World in Data based on three main sources: - - BP Statistical Review of World Energy. - - Ember Yearly Electricity Data (2023). - - Ember European Electricity Review (2022). + - [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + - [Ember Yearly Electricity Data (2023)](https://ember-climate.org/data-catalogue/yearly-electricity-data/). + - [Ember European Electricity Review (2022)](https://ember-climate.org/insights/research/european-electricity-review-2022/). Ember compile their global dataset from various sources including: - Eurostat: Annual European generation and import data, and monthly data in some cases where better sources are not available. @@ -18,16 +18,16 @@ dataset: - IRENA: Annual global capacity data for all non-fossil fuel types, and for Other Fossil where available. - WRI: Annual global capacity data for Other Fossil where other sources are not available. - European carbon intensities rely on data from the European Environment Agency (EEA). - - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found here. - - A complete list of data sources for each individual country in Ember's European Electricity Review can be found here. + - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found [here](https://ember-climate.org/app/uploads/2022/07/Ember-Electricity-Data-Methodology.pdf). + - A complete list of data sources for each individual country in Ember's European Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/02/EER-Methodology.pdf). We rely on Ember as the primary source of electricity consumption data. While BP provides primary energy (not just electricity) consumption data and it provides a longer time-series (dating back to 1965) than Ember (which only dates back to 1990), BP does not provide data for all countries or for all sources of electricity (for example, only Ember provides data on electricity from bioenergy). So, where data from Ember is available for a given country and year, we rely on it as the primary source. We then supplement this with data from BP where data from Ember is not available. Our World in Data has converted absolute electricity production by source to the share in the mix by dividing each by total electricity production. - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -53,36 +53,32 @@ dataset: * "North America" - All North American countries + "Other Caribbean" + "Other North America". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "Middle East (Ember)": Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates and Yemen. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - publication_year: 2022 - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Our World in Data based on Ember's Yearly Electricity Data (2023) - published_by: Ember - publication_year: 2023 - publication_date: 2023-01-31 - date_accessed: 2023-02-20 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Our World in Data based on Ember's European Electricity Review (2022) - published_by: Ember - publication_year: 2022 - publication_date: 2022-02-01 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + publication_year: 2022 + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Our World in Data based on Ember's Yearly Electricity Data (2023) + published_by: Ember + publication_year: 2023 + publication_date: 2023-01-31 + date_accessed: 2023-02-20 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Our World in Data based on Ember's European Electricity Review (2022) + published_by: Ember + publication_year: 2022 + publication_date: 2022-02-01 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: electricity_mix: variables: @@ -94,8 +90,8 @@ tables: name: Bioenergy bioenergy_share_of_electricity__pct: title: Bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy co2_intensity__gco2_kwh: @@ -112,8 +108,8 @@ tables: name: Coal coal_share_of_electricity__pct: title: Coal (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal fossil_generation__twh: @@ -124,8 +120,8 @@ tables: name: Fossil fuels fossil_share_of_electricity__pct: title: Fossil fuels (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil fuels gas_generation__twh: @@ -136,8 +132,8 @@ tables: name: Gas gas_share_of_electricity__pct: title: Gas (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro_generation__twh: @@ -148,8 +144,8 @@ tables: name: Hydropower hydro_share_of_electricity__pct: title: Hydro (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydropower low_carbon_generation__twh: @@ -160,14 +156,14 @@ tables: name: Low-carbon electricity low_carbon_share_of_electricity__pct: title: Low-carbon electricity (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Share of electricity from low-carbon sources net_imports_share_of_demand__pct: title: Net electricity imports as a share of demand (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Net electricity imports as a share of demand nuclear_generation__twh: @@ -178,8 +174,8 @@ tables: name: Nuclear nuclear_share_of_electricity__pct: title: Nuclear (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear oil_generation__twh: @@ -190,8 +186,8 @@ tables: name: Oil oil_share_of_electricity__pct: title: Oil (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Oil other_renewables_excluding_bioenergy_generation__twh: @@ -202,8 +198,8 @@ tables: name: Other renewables, excluding bioenergy other_renewables_excluding_bioenergy_share_of_electricity__pct: title: Other renewables excluding bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, excluding bioenergy other_renewables_including_bioenergy_generation__twh: @@ -214,8 +210,8 @@ tables: name: Other renewables, including bioenergy other_renewables_including_bioenergy_share_of_electricity__pct: title: Other renewables including bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, including bioenergy per_capita_bioenergy_generation__kwh: @@ -343,8 +339,8 @@ tables: name: Renewables renewable_share_of_electricity__pct: title: Renewables (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables numDecimalPlaces: 2 @@ -362,14 +358,14 @@ tables: name: Solar and wind solar_share_of_electricity__pct: title: Solar (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar solar_and_wind_share_of_electricity__pct: title: Solar and wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar and wind total_demand__twh: @@ -380,8 +376,8 @@ tables: name: Electricity demand total_electricity_share_of_primary_energy__pct: title: Electricity as share of primary energy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Electricity as share of primary energy total_emissions__mtco2: @@ -410,7 +406,7 @@ tables: name: Wind wind_share_of_electricity__pct: title: Wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind diff --git a/etl/steps/archive/garden/energy/2023-02-20/fossil_fuel_production.meta.yml b/etl/steps/archive/garden/energy/2023-02-20/fossil_fuel_production.meta.yml index a14ff8f9944..019333dba95 100644 --- a/etl/steps/archive/garden/energy/2023-02-20/fossil_fuel_production.meta.yml +++ b/etl/steps/archive/garden/energy/2023-02-20/fossil_fuel_production.meta.yml @@ -4,7 +4,7 @@ dataset: title: Fossil fuel production (BP & Shift, 2023) short_name: fossil_fuel_production description: | - This dataset on fossil fuel production is generated by combining the latest data from the BP Statistical Review of World Energy and The Shift Dataportal. + This dataset on fossil fuel production is generated by combining the latest data from [the BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [The Shift Dataportal](https://www.theshiftdataportal.org/energy). BP provide fossil fuel production data from 1965 onwards (and crude prices from 1861 onwards). The Shift Dataportal provides long-term data from 1900, but only extends to 2016. @@ -12,127 +12,124 @@ dataset: We have converted primary production in exajoules to terawatt-hours using the conversion factor: 1,000,000 / 3,600 ~ 278. - Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + description: | + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: - * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. - * "Australasia (BP)": Australia, New Zealand. - * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. - * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. - * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama - * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. - * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. - * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. - * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. - * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. - * "North America (BP)": US (excluding US territories), Canada, Mexico - * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. - * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. - * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. - * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. - * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. - * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. - - Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: - * "Africa" - All African countries + "Other Africa". - * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". - * "Europe" - All European countries + "Other Europe". - * "North America" - All North American countries + "Other Caribbean" + "Other North America". - * "Oceania" - All Oceanian countries. - * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. - - - name: Our World in Data based on The Shift Dataportal (2022) - published_by: The Shift Dataportal - date_accessed: 2022-07-18 - url: https://www.theshiftdataportal.org/energy + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: + * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. + * "Australasia (BP)": Australia, New Zealand. + * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. + * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. + * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama + * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. + * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. + * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. + * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. + * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. + * "North America (BP)": US (excluding US territories), Canada, Mexico + * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. + * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. + * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. + * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. + * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. + * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. + Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: + * "Africa" - All African countries + "Other Africa". + * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". + * "Europe" - All European countries + "Other Europe". + * "North America" - All North American countries + "Other Caribbean" + "Other North America". + * "Oceania" - All Oceanian countries. + * "South America" - All South American countries + "Other South America". + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). + - name: Our World in Data based on The Shift Dataportal (2022) + published_by: The Shift Dataportal + date_accessed: 2022-07-18 + url: https://www.theshiftdataportal.org/energy tables: fossil_fuel_production: variables: annual_change_in_coal_production__pct: - title: "Annual change in coal production (%)" - short_unit: "%" - unit: "%" + title: Annual change in coal production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_coal_production__twh: - title: "Annual change in coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_gas_production__pct: - title: "Annual change in gas production (%)" - short_unit: "%" - unit: "%" + title: Annual change in gas production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_gas_production__twh: - title: "Annual change in gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_oil_production__pct: - title: "Annual change in oil production (%)" - short_unit: "%" - unit: "%" + title: Annual change in oil production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in oil production" + name: Annual change in oil production annual_change_in_oil_production__twh: - title: "Annual change in oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in oil production" + name: Annual change in oil production coal_production__twh: - title: "Coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Coal production" + name: Coal production numDecimalPlaces: 0 coal_production_per_capita__kwh: - title: "Coal production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Coal production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Coal production per capita" + name: Coal production per capita numDecimalPlaces: 0 gas_production__twh: - title: "Gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Gas production" + name: Gas production numDecimalPlaces: 0 gas_production_per_capita__kwh: - title: "Gas production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Gas production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Gas production per capita" + name: Gas production per capita numDecimalPlaces: 0 oil_production__twh: - title: "Oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Oil production" + name: Oil production numDecimalPlaces: 0 oil_production_per_capita__kwh: - title: "Oil production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Oil production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Oil production per capita" + name: Oil production per capita numDecimalPlaces: 0 diff --git a/etl/steps/archive/garden/energy/2023-02-20/owid_energy.meta.yml b/etl/steps/archive/garden/energy/2023-02-20/owid_energy.meta.yml index 76b3c2e6264..a684fa8a9c2 100644 --- a/etl/steps/archive/garden/energy/2023-02-20/owid_energy.meta.yml +++ b/etl/steps/archive/garden/energy/2023-02-20/owid_energy.meta.yml @@ -6,7 +6,7 @@ dataset: description: | OWID Energy dataset. - This dataset will be loaded by the energy-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the energy-data repository](https://github.com/owid/energy-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' metadata and the content of owid_energy_variable_mapping.csv. diff --git a/etl/steps/archive/garden/energy/2023-02-20/primary_energy_consumption.meta.yml b/etl/steps/archive/garden/energy/2023-02-20/primary_energy_consumption.meta.yml index 2f128994faa..b32d357b973 100644 --- a/etl/steps/archive/garden/energy/2023-02-20/primary_energy_consumption.meta.yml +++ b/etl/steps/archive/garden/energy/2023-02-20/primary_energy_consumption.meta.yml @@ -5,73 +5,69 @@ dataset: short_name: primary_energy_consumption description: | Primary energy consumption data was compiled by Our World in Data based on two key data sources: - 1. BP Statistical Review of World Energy. - 2. International energy data from the U.S. Energy Information Administration (EIA). + 1. [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + 2. [International energy data from the U.S. Energy Information Administration (EIA)](https://www.eia.gov/international/data/world/total-energy/more-total-energy-data). BP provides the longest and most up-to-date time-series of primary energy. However, it does not provide data for all countries. We have therefore supplemented this dataset with energy data from the EIA. Where BP provides data for a given country, this data is adopted; for countries where this data is missing, we rely on EIA energy figures. - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). - To calculate energy per unit of GDP, we use total real GDP figures from the Maddison Project Database, version 2020. + To calculate energy per unit of GDP, we use total real GDP figures from [the Maddison Project Database, version 2020](https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020). This dataset is based on Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update ”. GDP is measured in 2011$ which are PPP-adjusted. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - description: | - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + description: | + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: - * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. - * "Australasia (BP)": Australia, New Zealand. - * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. - * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. - * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama - * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. - * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. - * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. - * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. - * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. - * "North America (BP)": US (excluding US territories), Canada, Mexico - * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. - * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. - * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. - * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. - * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. - * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: + * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. + * "Australasia (BP)": Australia, New Zealand. + * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. + * "Caribbean (BP)": Atlantic islands between the US Gulf Coast and South America, including Puerto Rico, US Virgin Islands and Bermuda. + * "Central America (BP)": Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama + * "Eastern Africa (BP)": Territories on the east coast of Africa from Sudan to Mozambique. Also Madagascar, Malawi, Uganda, Zambia, Zimbabwe. + * "Europe (BP)": European members of the OECD plus Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Cyprus, Georgia, Gibraltar, Latvia, Lithuania, Malta, Montenegro, North Macedonia, Romania, Serbia and Ukraine. + * "Middle Africa (BP)": Angola, Cameroon, Central African Republic, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe. + * "Middle East (BP)": Arabian Peninsula, Iran, Iraq, Israel, Jordan, Lebanon, Syria. + * "Non-OECD (BP)" - Organization for Economic Co-operation and Development: All countries that are not members of the OECD. + * "North America (BP)": US (excluding US territories), Canada, Mexico + * "Northern Africa (BP)": Territories on the north coast of Africa from Egypt to Western Sahara. + * "OECD (BP)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, US. + * "OPEC (BP)" - Organization of the Petroleum Exporting Countries: Iran, Iraq, Kuwait, Saudi Arabia, United Arab Emirates, Algeria, Libya, Angola, Equatorial Guinea, Gabon, Nigeria, Republic of Congo, Venezuela. + * "South and Central America (BP)": Caribbean (including Puerto Rico and US Virgin Islands), Bermuda, Central and South America. + * "Southern Africa (BP)": Botswana, Lesotho, Namibia, South Africa, Swaziland. + * "Western Africa (BP)": Territories on the west coast of Africa from Mauritania to Nigeria, including Burkina Faso, Cape Verde, Mali and Niger. - Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: - * "Africa" - All African countries + "Other Africa". - * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". - * "Europe" - All European countries + "Other Europe". - * "North America" - All North American countries + "Other Caribbean" + "Other North America". - * "Oceania" - All Oceanian countries. - * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. - - - name: Our World in Data based on EIA International energy data (2022) - published_by: U.S. Energy Information Administration (EIA) - date_accessed: 2022-07-27 - url: https://www.eia.gov/opendata/bulkfiles.php - description: | - Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their Bulk Download Facility. - - EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with our region definitions). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - - - name: Maddison Project Database 2020 (Bolt and van Zanden, 2020) - published_by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update“. - date_accessed: 2022-04-12 - url: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 + Additionally, BP includes some regions that are not explicitly defined (e.g. "Other Europe", or "Other CIS"). We define our regions in the following way: + * "Africa" - All African countries + "Other Africa". + * "Asia" - All Asian countries + "Other Middle East" + "Other CIS" + "Other Asia Pacific". + * "Europe" - All European countries + "Other Europe". + * "North America" - All North American countries + "Other Caribbean" + "Other North America". + * "Oceania" - All Oceanian countries. + * "South America" - All South American countries + "Other South America". + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). + - name: Our World in Data based on EIA International energy data (2022) + published_by: U.S. Energy Information Administration (EIA) + date_accessed: 2022-07-27 + url: https://www.eia.gov/opendata/bulkfiles.php + description: | + Total energy consumption, extracted from EIA's international energy data from the EIA, downloaded using their [Bulk Download Facility](https://www.eia.gov/opendata/bulkfiles.php). + EIA's region definitions sometimes differ from Our World in Data's definitions. For example, in EIA's data, Russia is not included in Europe, whereas Our World in Data includes Russia in Europe (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "Europe (EIA)" to refer to EIA's original data using their definition of the region, as well as "Europe", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + - name: Maddison Project Database 2020 (Bolt and van Zanden, 2020) + published_by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update“. + date_accessed: 2022-04-12 + url: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 tables: primary_energy_consumption: variables: annual_change_in_primary_energy_consumption__pct: title: Annual change in primary energy consumption (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Annual change in primary energy consumption annual_change_in_primary_energy_consumption__twh: @@ -84,7 +80,9 @@ tables: title: GDP short_unit: $ unit: 2011 int-$ - description: Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over + time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. display: numDecimalPlaces: 0 population: diff --git a/etl/steps/archive/garden/energy/2023-02-20/uk_historical_electricity.meta.yml b/etl/steps/archive/garden/energy/2023-02-20/uk_historical_electricity.meta.yml index d402b4068be..ce5838830bc 100644 --- a/etl/steps/archive/garden/energy/2023-02-20/uk_historical_electricity.meta.yml +++ b/etl/steps/archive/garden/energy/2023-02-20/uk_historical_electricity.meta.yml @@ -4,33 +4,28 @@ dataset: title: UK historical electricity (DUKES, 2023) short_name: uk_historical_electricity description: | - All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy. + All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from [the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy](https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes). - All other data is sourced from the BP's Statistical Review of World Energy and Ember's Yearly Electricity Data. Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. + All other data is sourced from the [BP's Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [Ember's Yearly Electricity Data](https://ember-climate.org/data-catalogue/yearly-electricity-data/). Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. sources: - - - name: Digest of UK Energy Statistics - published_by: UK's Department for Business, Energy & Industrial Strategy - date_accessed: 2022-09-21 - url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data - - - name: BP Statistical Review of World Energy - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Ember's Yearly Electricity Data - published_by: Ember - publication_year: 2023 - date_accessed: 2023-02-20 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Ember's European Electricity Review - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Digest of UK Energy Statistics + published_by: UK's Department for Business, Energy & Industrial Strategy + date_accessed: 2022-09-21 + url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data + - name: BP Statistical Review of World Energy + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Ember's Yearly Electricity Data + published_by: Ember + publication_year: 2023 + date_accessed: 2023-02-20 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Ember's European Electricity Review + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: uk_historical_electricity: variables: diff --git a/etl/steps/archive/garden/energy/2023-06-01/electricity_mix.meta.yml b/etl/steps/archive/garden/energy/2023-06-01/electricity_mix.meta.yml index 59d35762173..927e7973624 100644 --- a/etl/steps/archive/garden/energy/2023-06-01/electricity_mix.meta.yml +++ b/etl/steps/archive/garden/energy/2023-06-01/electricity_mix.meta.yml @@ -2,9 +2,9 @@ dataset: title: Electricity mix (BP & Ember, 2023b) description: | Data is compiled by Our World in Data based on three main sources: - - BP Statistical Review of World Energy. - - Ember Yearly Electricity Data (2023). - - Ember European Electricity Review (2022). + - [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + - [Ember Yearly Electricity Data (2023)](https://ember-climate.org/data-catalogue/yearly-electricity-data/). + - [Ember European Electricity Review (2022)](https://ember-climate.org/insights/research/european-electricity-review-2022/). Ember compile their global dataset from various sources including: - Eurostat: Annual European generation and import data, and monthly data in some cases where better sources are not available. @@ -15,16 +15,16 @@ dataset: - IRENA: Annual global capacity data for all non-fossil fuel types, and for Other Fossil where available. - WRI: Annual global capacity data for Other Fossil where other sources are not available. - European carbon intensities rely on data from the European Environment Agency (EEA). - - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found here. - - A complete list of data sources for each individual country in Ember's European Electricity Review can be found here. + - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found [here](https://ember-climate.org/app/uploads/2022/07/Ember-Electricity-Data-Methodology.pdf). + - A complete list of data sources for each individual country in Ember's European Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/02/EER-Methodology.pdf). We rely on Ember as the primary source of electricity consumption data. While BP provides primary energy (not just electricity) consumption data and it provides a longer time-series (dating back to 1965) than Ember (which only dates back to 1990), BP does not provide data for all countries or for all sources of electricity (for example, only Ember provides data on electricity from bioenergy). So, where data from Ember is available for a given country and year, we rely on it as the primary source. We then supplement this with data from BP where data from Ember is not available. Our World in Data has converted absolute electricity production by source to the share in the mix by dividing each by total electricity production. - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -50,15 +50,14 @@ dataset: * "North America" - All North American countries + "Other Caribbean" + "Other North America". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa" is included in "Other Africa"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "Middle East (Ember)": Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates and Yemen. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. - tables: electricity_mix: variables: @@ -70,14 +69,14 @@ tables: name: Bioenergy bioenergy_share_of_electricity__pct: title: Bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy co2_intensity__gco2_kwh: title: Carbon intensity of electricity (gCO2/kWh) - short_unit: gCO₂ - unit: grams of CO₂ equivalent per kilowatt-hour + short_unit: "gCO₂" + unit: "grams of CO₂ equivalent per kilowatt-hour" display: name: Carbon intensity of electricity per kilowatt-hour coal_generation__twh: @@ -88,8 +87,8 @@ tables: name: Coal coal_share_of_electricity__pct: title: Coal (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal fossil_generation__twh: @@ -100,8 +99,8 @@ tables: name: Fossil fuels fossil_share_of_electricity__pct: title: Fossil fuels (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil fuels gas_generation__twh: @@ -112,8 +111,8 @@ tables: name: Gas gas_share_of_electricity__pct: title: Gas (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro_generation__twh: @@ -124,8 +123,8 @@ tables: name: Hydropower hydro_share_of_electricity__pct: title: Hydro (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydropower low_carbon_generation__twh: @@ -136,14 +135,14 @@ tables: name: Low-carbon electricity low_carbon_share_of_electricity__pct: title: Low-carbon electricity (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Share of electricity from low-carbon sources net_imports_share_of_demand__pct: title: Net electricity imports as a share of demand (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Net electricity imports as a share of demand nuclear_generation__twh: @@ -154,8 +153,8 @@ tables: name: Nuclear nuclear_share_of_electricity__pct: title: Nuclear (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear oil_generation__twh: @@ -166,8 +165,8 @@ tables: name: Oil oil_share_of_electricity__pct: title: Oil (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Oil other_renewables_excluding_bioenergy_generation__twh: @@ -178,8 +177,8 @@ tables: name: Other renewables, excluding bioenergy other_renewables_excluding_bioenergy_share_of_electricity__pct: title: Other renewables excluding bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, excluding bioenergy other_renewables_including_bioenergy_generation__twh: @@ -190,8 +189,8 @@ tables: name: Other renewables, including bioenergy other_renewables_including_bioenergy_share_of_electricity__pct: title: Other renewables including bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, including bioenergy per_capita_bioenergy_generation__kwh: @@ -319,8 +318,8 @@ tables: name: Renewables renewable_share_of_electricity__pct: title: Renewables (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables numDecimalPlaces: 2 @@ -338,14 +337,14 @@ tables: name: Solar and wind solar_share_of_electricity__pct: title: Solar (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar solar_and_wind_share_of_electricity__pct: title: Solar and wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar and wind total_demand__twh: @@ -356,8 +355,8 @@ tables: name: Electricity demand total_electricity_share_of_primary_energy__pct: title: Electricity as share of primary energy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Electricity as share of primary energy total_emissions__mtco2: @@ -386,7 +385,7 @@ tables: name: Wind wind_share_of_electricity__pct: title: Wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind diff --git a/etl/steps/archive/garden/energy/2023-06-01/fossil_fuel_production.meta.yml b/etl/steps/archive/garden/energy/2023-06-01/fossil_fuel_production.meta.yml index 8deca18c3fd..1da62f05000 100644 --- a/etl/steps/archive/garden/energy/2023-06-01/fossil_fuel_production.meta.yml +++ b/etl/steps/archive/garden/energy/2023-06-01/fossil_fuel_production.meta.yml @@ -1,7 +1,7 @@ dataset: title: Fossil fuel production (BP & Shift, 2023b) description: | - This dataset on fossil fuel production is generated by combining the latest data from the BP Statistical Review of World Energy and The Shift Dataportal. + This dataset on fossil fuel production is generated by combining the latest data from [the BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [The Shift Dataportal](https://www.theshiftdataportal.org/energy). BP provide fossil fuel production data from 1965 onwards (and crude prices from 1861 onwards). The Shift Dataportal provides long-term data from 1900, but only extends to 2016. @@ -9,86 +9,85 @@ dataset: We have converted primary production in exajoules to terawatt-hours using the conversion factor: 1,000,000 / 3,600 ~ 278. - Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. - + Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). tables: fossil_fuel_production: variables: annual_change_in_coal_production__pct: - title: "Annual change in coal production (%)" - short_unit: "%" - unit: "%" + title: Annual change in coal production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_coal_production__twh: - title: "Annual change in coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_gas_production__pct: - title: "Annual change in gas production (%)" - short_unit: "%" - unit: "%" + title: Annual change in gas production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_gas_production__twh: - title: "Annual change in gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_oil_production__pct: - title: "Annual change in oil production (%)" - short_unit: "%" - unit: "%" + title: Annual change in oil production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in oil production" + name: Annual change in oil production annual_change_in_oil_production__twh: - title: "Annual change in oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in oil production" + name: Annual change in oil production coal_production__twh: - title: "Coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Coal production" + name: Coal production numDecimalPlaces: 0 coal_production_per_capita__kwh: - title: "Coal production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Coal production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Coal production per capita" + name: Coal production per capita numDecimalPlaces: 0 gas_production__twh: - title: "Gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Gas production" + name: Gas production numDecimalPlaces: 0 gas_production_per_capita__kwh: - title: "Gas production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Gas production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Gas production per capita" + name: Gas production per capita numDecimalPlaces: 0 oil_production__twh: - title: "Oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Oil production" + name: Oil production numDecimalPlaces: 0 oil_production_per_capita__kwh: - title: "Oil production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Oil production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Oil production per capita" + name: Oil production per capita numDecimalPlaces: 0 diff --git a/etl/steps/archive/garden/energy/2023-06-01/owid_energy.meta.yml b/etl/steps/archive/garden/energy/2023-06-01/owid_energy.meta.yml index f57599a2b1f..46dba0e979d 100644 --- a/etl/steps/archive/garden/energy/2023-06-01/owid_energy.meta.yml +++ b/etl/steps/archive/garden/energy/2023-06-01/owid_energy.meta.yml @@ -3,7 +3,7 @@ dataset: description: | OWID Energy dataset. - This dataset will be loaded by the energy-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the energy-data repository](https://github.com/owid/energy-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' metadata and the content of owid_energy_variable_mapping.csv. diff --git a/etl/steps/archive/garden/energy/2023-06-01/primary_energy_consumption.meta.yml b/etl/steps/archive/garden/energy/2023-06-01/primary_energy_consumption.meta.yml index b639cbdabb2..94f7d7ad975 100644 --- a/etl/steps/archive/garden/energy/2023-06-01/primary_energy_consumption.meta.yml +++ b/etl/steps/archive/garden/energy/2023-06-01/primary_energy_consumption.meta.yml @@ -2,23 +2,22 @@ dataset: title: Primary energy consumption (BP & EIA, 2023b) description: | Primary energy consumption data was compiled by Our World in Data based on two key data sources: - 1. BP Statistical Review of World Energy. - 2. International energy data from the U.S. Energy Information Administration (EIA). + 1. [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + 2. [International energy data from the U.S. Energy Information Administration (EIA)](https://www.eia.gov/international/data/world/total-energy/more-total-energy-data). BP provides the longest and most up-to-date time-series of primary energy. However, it does not provide data for all countries. We have therefore supplemented this dataset with energy data from the EIA. Where BP provides data for a given country, this data is adopted; for countries where this data is missing, we rely on EIA energy figures. - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). - To calculate energy per unit of GDP, we use total real GDP figures from the Maddison Project Database, version 2020. + To calculate energy per unit of GDP, we use total real GDP figures from [the Maddison Project Database, version 2020](https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020). This dataset is based on Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update ”. GDP is measured in 2011$ which are PPP-adjusted. - tables: primary_energy_consumption: variables: annual_change_in_primary_energy_consumption__pct: title: Annual change in primary energy consumption (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Annual change in primary energy consumption annual_change_in_primary_energy_consumption__twh: @@ -31,7 +30,9 @@ tables: title: GDP short_unit: $ unit: 2011 int-$ - description: Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over + time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. display: numDecimalPlaces: 0 population: diff --git a/etl/steps/archive/garden/energy/2023-06-01/uk_historical_electricity.meta.yml b/etl/steps/archive/garden/energy/2023-06-01/uk_historical_electricity.meta.yml index eb54240e8cd..69b8f77b574 100644 --- a/etl/steps/archive/garden/energy/2023-06-01/uk_historical_electricity.meta.yml +++ b/etl/steps/archive/garden/energy/2023-06-01/uk_historical_electricity.meta.yml @@ -1,10 +1,9 @@ dataset: title: UK historical electricity (DUKES, 2023b) description: | - All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy. - - All other data is sourced from the BP's Statistical Review of World Energy and Ember's Yearly Electricity Data. Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. + All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from [the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy](https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes). + All other data is sourced from the [BP's Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [Ember's Yearly Electricity Data](https://ember-climate.org/data-catalogue/yearly-electricity-data/). Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. tables: uk_historical_electricity: variables: diff --git a/etl/steps/archive/garden/gcp/2022-09-29/global_carbon_budget_additional.meta.yml b/etl/steps/archive/garden/gcp/2022-09-29/global_carbon_budget_additional.meta.yml index 42842c8f29d..d2f2462dfac 100644 --- a/etl/steps/archive/garden/gcp/2022-09-29/global_carbon_budget_additional.meta.yml +++ b/etl/steps/archive/garden/gcp/2022-09-29/global_carbon_budget_additional.meta.yml @@ -1,25 +1,23 @@ dataset: title: Global Carbon Budget (Global Carbon Project, v2021b) sources: - - - name: Global Carbon Project (2021) - published_by: Global Carbon Budget - Global Carbon Project (2021) - description: | - The Global Carbon Budget dataset is available here and here. + - name: Global Carbon Project (2021) + published_by: Global Carbon Budget - Global Carbon Project (2021) + description: | + The Global Carbon Budget dataset is available [here](https://www.icos-cp.eu/science-and-impact/global-carbon-budget/2021) and [here](https://doi.org/10.5281/zenodo.5569235). - Variables include each country, region and World Bank income group's share of the global population; production-based (territorial); and consumption-based (trade-adjusted) carbon dioxide emissions. + Variables include each country, region and World Bank income group's share of the global population; production-based (territorial); and consumption-based (trade-adjusted) carbon dioxide emissions. - This was calculated by Our World in Data based on CO₂ figures produced by the Global Carbon Project. This is given as production (territorial) emissions in addition to trade-adjusted consumption-based emissions. Consumption-based emissions are national or regional emissions which have been adjusted for trade (i.e. territorial/production emissions minus emissions embedded in exports, plus emissions embedded in imports). If a country's consumption-based emissions are higher than its production emissions it is a net importer of carbon dioxide. + This was calculated by Our World in Data based on CO₂ figures produced by the Global Carbon Project. This is given as production (territorial) emissions in addition to trade-adjusted consumption-based emissions. Consumption-based emissions are national or regional emissions which have been adjusted for trade (i.e. territorial/production emissions minus emissions embedded in exports, plus emissions embedded in imports). If a country's consumption-based emissions are higher than its production emissions it is a net importer of carbon dioxide. - Note that consumption-based emissions are not available for all countries; although those without complete data are a small fraction (3%) of the global total. Each country's share of world emissions are based on the share of the global total minus categories termed 'bunkers' and 'statistical differences' (which include cross-boundary emissions such as international travel and shipping. + Note that consumption-based emissions are not available for all countries; although those without complete data are a small fraction (3%) of the global total. Each country's share of world emissions are based on the share of the global total minus categories termed 'bunkers' and 'statistical differences' (which include cross-boundary emissions such as international travel and shipping. - Calculation of each country's share of the global population is calculated using our population dataset, based on different sources). + Calculation of each country's share of the global population is calculated using our population dataset, based on [different sources](https://ourworldindata.org/population-sources)). - Data on global emissions has been converted by Our World in Data from tonnes of carbon to tonnes of carbon dioxide (CO₂) using a conversion factor of 3.664. - - The full reference for the Carbon Budget 2021 is: - Global Carbon Budget 2021, by Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle and Jiye Zeng (2022), Earth System Science Data, 14, 1917–2005, 2022, DOI: 10.5194/essd-14-1917-2022. + Data on global emissions has been converted by Our World in Data from tonnes of carbon to tonnes of carbon dioxide (CO₂) using a conversion factor of 3.664. + The full reference for the Carbon Budget 2021 is: + [Global Carbon Budget 2021](https://doi.org/10.5194/essd-14-1917-2022), by Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle and Jiye Zeng (2022), Earth System Science Data, 14, 1917–2005, 2022, DOI: 10.5194/essd-14-1917-2022. tables: global_carbon_budget_additional: variables: @@ -29,14 +27,14 @@ tables: short_unit: t consumption_emissions_as_share_of_global: title: "Consumption-based CO₂ emissions (% of global total)" - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' consumption_emissions_per_capita: title: "Consumption-based CO₂ per capita" unit: tonnes of CO₂ per capita short_unit: t global_bunker_emissions: - title: "Global bunker emissions" + title: Global bunker emissions unit: tonnes short_unit: t global_fossil_emissions: @@ -55,17 +53,17 @@ tables: short_unit: t description: "Global CO₂ emissions from land use change." global_population: - title: "Global population" + title: Global population unit: persons short_unit: persons population: - title: "Population" + title: Population unit: persons short_unit: persons population_as_share_of_global: title: Share of global population - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' production_emissions: title: "Production-based CO₂ emissions" unit: tonnes diff --git a/etl/steps/archive/garden/gcp/2022-11-11/global_carbon_budget.meta.yml b/etl/steps/archive/garden/gcp/2022-11-11/global_carbon_budget.meta.yml index ef45c542109..4668cd55152 100644 --- a/etl/steps/archive/garden/gcp/2022-11-11/global_carbon_budget.meta.yml +++ b/etl/steps/archive/garden/gcp/2022-11-11/global_carbon_budget.meta.yml @@ -3,10 +3,10 @@ dataset: short_name: global_carbon_budget title: Global Carbon Budget (Global Carbon Project, 2022) description: | - The Global Carbon Budget dataset is available here. + The Global Carbon Budget dataset is available [here](https://globalcarbonbudget.org/archive/). Full reference: - Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811-4900, https://doi.org/10.5194/essd-14-4811-2022, 2022. + Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811-4900, https://doi.org/10.5194/essd-14-4811-2022, 2022. Variables include each country, region and World Bank income group's share of the global population; production-based (territorial); and consumption-based (trade-adjusted) carbon dioxide emissions. @@ -14,7 +14,7 @@ dataset: Note that consumption-based emissions are not available for all countries; although those without complete data are a small fraction (3%) of the global total. Each country's share of world emissions are based on the share of the global total minus categories termed 'bunkers' and 'statistical differences' (which include cross-boundary emissions such as international travel and shipping. - Calculation of each country's share of the global population is calculated using our population dataset, based on different sources). + Calculation of each country's share of the global population is calculated using our population dataset, based on [different sources](https://ourworldindata.org/population-sources)). Data on global emissions has been converted by Our World in Data from tonnes of carbon to tonnes of carbon dioxide (CO₂) using a conversion factor of 3.664. @@ -313,7 +313,9 @@ tables: title: "GDP" unit: "2011 international-$" short_unit: "$" - description: "Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries." + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) + and price differences between countries. global_cumulative_emissions_from_cement: title: "Global cumulative CO₂ emissions from cement" unit: "tonnes" diff --git a/etl/steps/archive/garden/gcp/2023-04-28/global_carbon_budget.meta.yml b/etl/steps/archive/garden/gcp/2023-04-28/global_carbon_budget.meta.yml index d69c0584f73..42f40dd8a28 100644 --- a/etl/steps/archive/garden/gcp/2023-04-28/global_carbon_budget.meta.yml +++ b/etl/steps/archive/garden/gcp/2023-04-28/global_carbon_budget.meta.yml @@ -1,10 +1,10 @@ dataset: title: Global Carbon Budget (Global Carbon Project, 2023) description: | - The Global Carbon Budget dataset is available here. + The Global Carbon Budget dataset is available [here](https://globalcarbonbudget.org/archive/). Full reference: - Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811-4900, https://doi.org/10.5194/essd-14-4811-2022, 2022. + Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811-4900, https://doi.org/10.5194/essd-14-4811-2022, 2022. Variables include each country, region and World Bank income group's share of the global population; production-based (territorial); and consumption-based (trade-adjusted) carbon dioxide emissions. @@ -12,7 +12,7 @@ dataset: Note that consumption-based emissions are not available for all countries; although those without complete data are a small fraction (3%) of the global total. - Calculation of each country's share of the global population is calculated using our population dataset, based on different sources). + Calculation of each country's share of the global population is calculated using our population dataset, based on [different sources]("https://ourworldindata.org/population-sources)). Data on global emissions has been converted by Our World in Data from tonnes of carbon to tonnes of carbon dioxide (CO₂) using a conversion factor of 3.664. @@ -310,7 +310,9 @@ tables: title: "GDP" unit: "2011 international-$" short_unit: "$" - description: "Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries." + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time + (inflation) and price differences between countries. global_cumulative_emissions_from_cement: title: "Global cumulative CO₂ emissions from cement" unit: "tonnes" diff --git a/etl/steps/archive/garden/papers/2023-01-04/farmer_lafond_2016.meta.yml b/etl/steps/archive/garden/papers/2023-01-04/farmer_lafond_2016.meta.yml index a6083a834aa..1ddc2bf061d 100644 --- a/etl/steps/archive/garden/papers/2023-01-04/farmer_lafond_2016.meta.yml +++ b/etl/steps/archive/garden/papers/2023-01-04/farmer_lafond_2016.meta.yml @@ -71,7 +71,7 @@ dataset: + Vinyl chloride is measured in 1966 USD/lbs. + Wind turbine (Denmark) is measured in DKK/kW. - According to Farmer & Lafond (2016), the data are mostly taken from the Santa-Fe Performance Curve Database. The database has been constructed from personal communications and from Colpier and Cornland (2002), Goldemberg et al. (2004), Lieberman (1984), Lipman and Sperling (1999), Zhao (1999), McDonald and Schrattenholzer (2001), Neij et al. (2003), Moore (2006), Nemet (2006), Schilling and Esmundo (2009). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from Koomey and Hultman (2007) and Cooper (2009). The DNA sequencing data is from Wetterstrand (2015) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. + According to Farmer & Lafond (2016), the data are mostly taken from the Santa-Fe [Performance Curve Database](https://pcdb.santafe.edu/). The database has been constructed from personal communications and from [Colpier and Cornland (2002)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0095), [Goldemberg et al. (2004)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0130), [Lieberman (1984)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0180), [Lipman and Sperling (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0190), [Zhao (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0310), [McDonald and Schrattenholzer (2001)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0205), [Neij et al. (2003)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0235), [Moore (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0215), [Nemet (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0240), [Schilling and Esmundo (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0265). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from [Koomey and Hultman (2007)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0165) and [Cooper (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0100). The DNA sequencing data is from [Wetterstrand (2015)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0290) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. licenses: - name: Creative Commons 4.0 url: https://www.sciencedirect.com/science/article/pii/S0048733315001699 diff --git a/etl/steps/archive/garden/rff/2022-09-14/emissions_weighted_carbon_price.meta.yml b/etl/steps/archive/garden/rff/2022-09-14/emissions_weighted_carbon_price.meta.yml index 6a5c42ba695..f60c3b175f8 100644 --- a/etl/steps/archive/garden/rff/2022-09-14/emissions_weighted_carbon_price.meta.yml +++ b/etl/steps/archive/garden/rff/2022-09-14/emissions_weighted_carbon_price.meta.yml @@ -14,125 +14,124 @@ dataset: - Each sector’s contribution to a country’s CO2 emissions (e.g. what percentage of a country’s emissions come from electricity, or road transport) They then weight each sector’s carbon price by the relevant sector’s contribution to CO2 emissions, and aggregate these figures to get an economy-wide weighted carbon price. - A full technical note on this methodology is provided by the authors here. - + A full technical note on this methodology is provided by the authors [here](https://www.rff.org/publications/working-papers/emissions-weighted-carbon-price-sources-and-methods/). sources: - - - name: Dolphin, Pollitt and Newbery (2020). Emissions-weighted Carbon Price. - published_by: "Dolphin, G., Pollitt, M. and Newbery, D. 2020. The political economy of carbon pricing: a panel analysis. Oxford Economic Papers 72(2): 472-500." - publication_year: 2022 - publication_date: 2022-01-18 - url: https://github.com/g-dolphin/ECP - + - name: Dolphin, Pollitt and Newbery (2020). Emissions-weighted Carbon Price. + published_by: >- + Dolphin, G., Pollitt, M. and Newbery, D. 2020. The political economy of carbon pricing: a panel analysis. + Oxford Economic Papers 72(2): 472-500. + publication_year: 2022 + publication_date: 2022-01-18 + url: https://github.com/g-dolphin/ECP tables: emissions_weighted_carbon_price: title: Emissions-weighted carbon price variables: co2_with_ets_as_share_of_co2: title: CO2 emissions covered by an ETS as a share of the country's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_ets_as_share_of_ghg: title: CO2 emissions covered by an ETS as a share of the country's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_ets_as_share_of_world_co2: title: CO2 emissions covered by an ETS as a share of the world's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_ets_as_share_of_world_ghg: title: CO2 emissions covered by an ETS as a share of the world's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_co2: title: CO2 emissions covered by a carbon tax as a share of the country's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_ghg: title: CO2 emissions covered by a carbon tax as a share of the country's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_world_co2: title: CO2 emissions covered by a carbon tax as a share of the world's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_world_ghg: title: CO2 emissions covered by a carbon tax as a share of the world's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_co2: title: CO2 emissions covered by a carbon tax or an ETS as a share of the country's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_ghg: title: CO2 emissions covered by a carbon tax or an ETS as a share of the country's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_world_co2: title: CO2 emissions covered by a carbon tax or an ETS as a share of the world's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_world_ghg: title: CO2 emissions covered by a carbon tax or an ETS as a share of the world's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 price_with_ets_weighted_by_share_of_co2: title: Average price on emissions covered by an ETS, weighted by the share of the country's CO2 emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_ets_weighted_by_share_of_ghg: title: Average price on emissions covered by an ETS, weighted by the share of the country's GHG emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_or_ets_weighted_by_share_of_co2: title: Average price on emissions covered by a carbon tax or an ETS, weighted by the share of the country's CO2 emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_or_ets_weighted_by_share_of_ghg: title: Average price on emissions covered by a carbon tax or an ETS, weighted by the share of the country's GHG emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_weighted_by_share_of_co2: title: Average price on emissions covered by a carbon tax, weighted by the share of the country's CO2 emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_weighted_by_share_of_ghg: title: Average price on emissions covered by a carbon tax, weighted by the share of the country's GHG emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 diff --git a/etl/steps/archive/garden/shift/2022-07-18/fossil_fuel_production.meta.yml b/etl/steps/archive/garden/shift/2022-07-18/fossil_fuel_production.meta.yml index 63cb862fe54..3adc234eaec 100644 --- a/etl/steps/archive/garden/shift/2022-07-18/fossil_fuel_production.meta.yml +++ b/etl/steps/archive/garden/shift/2022-07-18/fossil_fuel_production.meta.yml @@ -1,34 +1,33 @@ dataset: title: Fossil fuel production (Shift, 2022) description: | - Fossil fuel production, produced by Our World in Data based on data from The Shift Dataportal. + Fossil fuel production, produced by Our World in Data based on data from [The Shift Dataportal](https://www.theshiftdataportal.org/energy). sources: - - - name: Our World in Data based on The Shift Dataportal (2022) - published_by: The Shift Dataportal - date_accessed: 2022-07-18 - url: https://www.theshiftdataportal.org/energy + - name: Our World in Data based on The Shift Dataportal (2022) + published_by: The Shift Dataportal + date_accessed: 2022-07-18 + url: https://www.theshiftdataportal.org/energy tables: fossil_fuel_production: variables: coal: - title: "Coal production" - short_unit: "TWh" - unit: "terawatt-hours" + title: Coal production + short_unit: TWh + unit: terawatt-hours description: display: numDecimalPlaces: 0 gas: - title: "Gas production" - short_unit: "TWh" - unit: "terawatt-hours" + title: Gas production + short_unit: TWh + unit: terawatt-hours description: display: numDecimalPlaces: 0 oil: - title: "Oil production" - short_unit: "TWh" - unit: "terawatt-hours" + title: Oil production + short_unit: TWh + unit: terawatt-hours description: display: numDecimalPlaces: 0 diff --git a/etl/steps/data/garden/agriculture/2023-06-12/uk_long_term_yields.meta.yml b/etl/steps/data/garden/agriculture/2023-06-12/uk_long_term_yields.meta.yml index 56957b32875..54e5166d6bd 100644 --- a/etl/steps/data/garden/agriculture/2023-06-12/uk_long_term_yields.meta.yml +++ b/etl/steps/data/garden/agriculture/2023-06-12/uk_long_term_yields.meta.yml @@ -5,7 +5,7 @@ dataset: • Data from 1270 to 1870 is taken from Table 3.06 of Broadberry et al. (2015). The data in this table is based on the Medieval Accounts Database, the Early Modern Probate Inventories Database and the Modern Farm Accounts Database. Seed sown per acre from the Medieval and Modern Databases. Pulses for the modern period and all seeds sown for the early modern period are taken from Overton and Campbell (1996), Allen (2005). This comprises crop yield estimates only for England. For this dataset, we have assumed that yields in England are also representative of average UK yields. The data was given as decadal averages, and we have assumed, for each value, the middle year in each decade. - All values of yield in bushels per acre have been converted to tonnes per hectare, using the conversion factors given by the USDA for the different commodities. + All values of yield in bushels per acre have been converted to tonnes per hectare, using the conversion factors given by [the USDA](https://www.ers.usda.gov/webdocs/publications/41880/33132_ah697_002.pdf) for the different commodities. • Data from 1870 to 1960 is taken from Table 4 of Brassley (2000). The data in this table is based on the book "A hundred Years of British food and farming: a statistical survey", by H. F. Marks (ed. D. K. Britton, 1989). The data is provided over 5-year periods. We have assumed, for each value, the middle year in each 5-year set. diff --git a/etl/steps/data/garden/andrew/2019-12-03/co2_mitigation_curves.meta.yml b/etl/steps/data/garden/andrew/2019-12-03/co2_mitigation_curves.meta.yml index 3297de15427..357d28189a8 100644 --- a/etl/steps/data/garden/andrew/2019-12-03/co2_mitigation_curves.meta.yml +++ b/etl/steps/data/garden/andrew/2019-12-03/co2_mitigation_curves.meta.yml @@ -15,7 +15,7 @@ tables: For example, 'Start in 2010' marks the necessary future emissions pathway to have a >66% chance of keeping global average temperatures below 1.5°C warming if global CO2 emissions mitigation had started in 2010, very quickly peaking then falling. - Data is sourced from Robbie Andrew, and available for download here. + Data is sourced from Robbie Andrew, and available for download [here](http://folk.uio.no/roberan/t/global_mitigation_curves.shtml). Historical emissions to 2017 are sourced from CDIAC/Global Carbon Project, projection to 2018 from Global Carbon Project (Le Quéré et al. 2018). @@ -34,7 +34,7 @@ tables: For example, 'Start in 2010' marks the necessary future emissions pathway to have a >66% chance of keeping global average temperatures below 2°C warming if global CO2 emissions mitigation had started in 2010, very quickly peaking then falling. - Data is sourced from Robbie Andrew, and available for download here. + Data is sourced from Robbie Andrew, and available for download [here](http://folk.uio.no/roberan/t/global_mitigation_curves.shtml). Historical emissions to 2017 are sourced from CDIAC/Global Carbon Project, projection to 2018 from Global Carbon Project (Le Quéré et al. 2018). diff --git a/etl/steps/data/garden/artificial_intelligence/2023-06-14/ai_deepfakes.meta.yml b/etl/steps/data/garden/artificial_intelligence/2023-06-14/ai_deepfakes.meta.yml index 7c944b8f961..13110c54988 100644 --- a/etl/steps/data/garden/artificial_intelligence/2023-06-14/ai_deepfakes.meta.yml +++ b/etl/steps/data/garden/artificial_intelligence/2023-06-14/ai_deepfakes.meta.yml @@ -1,12 +1,13 @@ dataset: title: DeepFake detection (AI Index, 2023) description: > - Data from Li et al. (2022) via AI Index report on Celeb-DF, presently one of the most challenging deepfake detection benchmarks. + Data from Li et al. (2022) via AI Index report on Celeb-DF, presently one of the most challenging deepfake detection benchmarks. - The AI Index is an independent initiative at the Stanford University Institute for Human-Centered Artificial Intelligence. - The mission of the AI Index is “to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public to develop intuitions about the complex field of AI.” - Their flagship output is the annual AI Index Report, which has been published since 2017. + The AI Index is an independent initiative at the Stanford University Institute for Human-Centered Artificial Intelligence. + The mission of the AI Index is “to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, + executives, journalists, and the general public to develop intuitions about the complex field of AI.” Their flagship output + is the annual AI Index Report, which has been published since 2017. licenses: - name: Public domain url: https://aiindex.stanford.edu/wp-content/uploads/2023/04/HAI_AI-Index-Report_2023.pdf @@ -17,33 +18,44 @@ dataset: date_accessed: '2023-06-19' publication_date: '2023-05-19' publication_year: 2023 - published_by: Li et al. (2022) via the AI Index 2023 Annual Report, AI Index Steering Committee, Institute - for Human-Centered AI, Stanford University, Stanford, CA, April 2023 + published_by: Li et al. (2022) via the AI Index 2023 Annual Report, AI Index Steering Committee, Institute for Human-Centered + AI, Stanford University, Stanford, CA, April 2023 tables: ai_deepfakes: variables: area_under_curve_score__auc: title: Area Under Curve Score (AUC) description: > - The Area Under Curve Score (AUC), also known as the AUC-ROC (Receiver Operating Characteristic) score, is a popular evaluation metric used in machine learning and statistics to assess the performance of binary classification models. - - In binary classification, the goal is to predict whether an instance belongs to one class (positive) or another (negative) based on its features. The ROC curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various classification thresholds. The TPR is the ratio of true positives to the total number of actual positives, while the FPR is the ratio of false positives to the total number of actual negatives. - - The AUC is a measure of the overall performance of the classifier across all possible classification thresholds. It represents the probability that a randomly chosen positive instance will be ranked higher than a randomly chosen negative instance according to the classifier's predicted probabilities. The AUC score ranges from 0 to 1, where a score of 1 indicates a perfect classifier, and a score of 0.5 represents a classifier with no discriminatory power (equivalent to random guessing). - - Interpreting the AUC score: - - AUC = 1: Perfect classifier. The model has a clear separation between the positive and negative classes, correctly ranking all instances. - AUC > 0.5: Better than random guessing. The model has some discriminatory power and performs better than a random classifier. - AUC = 0.5: Random classifier. The model performs no better than flipping a coin and has no ability to distinguish between the classes. - AUC < 0.5: Inverted classifier. The model performs worse than random guessing, meaning it is making incorrect predictions. - The AUC score is widely used because it is insensitive to class imbalance and classification thresholds. It provides a single scalar value to compare different classifiers or evaluate the performance of a single classifier. Higher AUC scores generally indicate better classifier performance in terms of the trade-off between true positives and false positives. - - It's important to note that the AUC score is specific to binary classification problems and cannot be directly applied to multi-class classification tasks without modification. - - unit: 'Area under curve' + The Area Under Curve Score (AUC), also known as the AUC-ROC (Receiver Operating Characteristic) score, is a popular + evaluation metric used in machine learning and statistics to assess the performance of binary classification models. + + In binary classification, the goal is to predict whether an instance belongs to one class (positive) or another + (negative) based on its features. The ROC curve is created by plotting the true positive rate (TPR) against the + false positive rate (FPR) at various classification thresholds. The TPR is the ratio of true positives to the total + number of actual positives, while the FPR is the ratio of false positives to the total number of actual negatives. + + The AUC is a measure of the overall performance of the classifier across all possible classification thresholds. + It represents the probability that a randomly chosen positive instance will be ranked higher than a randomly chosen + negative instance according to the classifier's predicted probabilities. The AUC score ranges from 0 to 1, where + a score of 1 indicates a perfect classifier, and a score of 0.5 represents a classifier with no discriminatory power + (equivalent to random guessing). + + Interpreting the AUC score: + + AUC = 1: Perfect classifier. The model has a clear separation between the positive and negative classes, correctly + ranking all instances. + AUC > 0.5: Better than random guessing. The model has some discriminatory power and performs better than a random + classifier. + AUC = 0.5: Random classifier. The model performs no better than flipping a coin and has no ability to distinguish + between the classes. + AUC < 0.5: Inverted classifier. The model performs worse than random guessing, meaning it is making incorrect predictions. + The AUC score is widely used because it is insensitive to class imbalance and classification thresholds. It provides + a single scalar value to compare different classifiers or evaluate the performance of a single classifier. Higher + AUC scores generally indicate better classifier performance in terms of the trade-off between true positives and + false positives. + + It's important to note that the AUC score is specific to binary classification problems and cannot be directly applied + to multi-class classification tasks without modification. + unit: Area under curve display: numDecimalPlaces: 0 - - - diff --git a/etl/steps/data/garden/cait/2022-08-10/ghg_emissions_by_sector.meta.yml b/etl/steps/data/garden/cait/2022-08-10/ghg_emissions_by_sector.meta.yml index dcfff80376e..1d497d5aaa5 100644 --- a/etl/steps/data/garden/cait/2022-08-10/ghg_emissions_by_sector.meta.yml +++ b/etl/steps/data/garden/cait/2022-08-10/ghg_emissions_by_sector.meta.yml @@ -6,7 +6,7 @@ dataset: description: | Emissions are measured in tonnes of carbon dioxide equivalents (CO₂e), based on 100-year global warming potential factors for non-CO₂ gases. - Emissions are broken down by sector. Further information on sector definitions is available here. + Emissions are broken down by sector. Further information on sector definitions is available [here](https://ourworldindata.org/ghg-emissions-by-sector). sources: - name: Our World in Data based on Climate Analysis Indicators Tool (CAIT). diff --git a/etl/steps/data/garden/covid/latest/cases_and_deaths_who.meta.yml b/etl/steps/data/garden/covid/latest/cases_and_deaths_who.meta.yml index 11da3973d09..e1efa5602e4 100644 --- a/etl/steps/data/garden/covid/latest/cases_and_deaths_who.meta.yml +++ b/etl/steps/data/garden/covid/latest/cases_and_deaths_who.meta.yml @@ -1,27 +1,21 @@ dataset: - title: "COVID-19: Confirmed cases and deaths (WHO)" + title: 'COVID-19: Confirmed cases and deaths (WHO)' description: >- - Raw data on confirmed cases and deaths for all countries is sourced from the - WHO - COVID-19 Dashboard. + Raw data on confirmed cases and deaths for all countries is sourced from the [WHO COVID-19 Dashboard](https://covid19.who.int/data). - Our complete COVID-19 dataset is a collection of the COVID-19 data maintained - by Our World in Data. It - is updated daily and includes data on confirmed cases, deaths, hospitalizations, - and testing. + Our complete COVID-19 dataset is a collection of the COVID-19 data maintained by *Our World in Data*. **It is updated + daily** and includes data on confirmed cases, deaths, hospitalizations, and testing. - We have created a new description of all our data sources. You find it at our - GitHub repository here. - There you can download all of our data. + We have created a new description of all our data sources. You find it at our GitHub repository **[here](https://github.com/owid/covid-19-data/tree/master/public/data/)**. + There you can download all of our data. - The WHO licenses this data under CC BY-NC-SA 3.0 IGO. You can read more here. + The WHO licenses this data under CC BY-NC-SA 3.0 IGO. You can read more [here](https://www.who.int/about/policies/publishing/copyright). - Attribute the data as the "WHO COVID-19 Dashboard. Geneva: World Health Organization, - 2020. Available online: https://covid19.who.int/". + Attribute the data as the "WHO COVID-19 Dashboard. Geneva: World Health Organization, 2020. Available online: https://covid19.who.int/". sources: - name: World Health Organization url: https://covid19.who.int/data diff --git a/etl/steps/data/garden/covid/latest/decoupling_metrics.meta.yml b/etl/steps/data/garden/covid/latest/decoupling_metrics.meta.yml index 24054cf52b3..5ed1d20817c 100644 --- a/etl/steps/data/garden/covid/latest/decoupling_metrics.meta.yml +++ b/etl/steps/data/garden/covid/latest/decoupling_metrics.meta.yml @@ -1,50 +1,36 @@ dataset: - title: "COVID-19: Decoupling of metrics (various sources)" + title: 'COVID-19: Decoupling of metrics (various sources)' description: >- - By comparing the proportion of confirmed cases that result in hospital admissions, - ICU admissions, and deaths, to previous - waves – when the population was not vaccinated – we can learn something about - the protection that vaccination has provided + By comparing the proportion of confirmed cases that result in hospital admissions, ICU admissions, and deaths, to previous + waves – when the population was not vaccinated – we can learn something about the protection that vaccination has provided against severe outcomes. - This chart shows one way to do this. It visualizes the main COVID metrics relative - to the peak of the last wave. The - peak of the last wave happened before the population was widely vaccinated. - In this representation of the data, if confirmed - cases increase but hospitalizations and deaths increase to a lesser extent, - it will mean that the many reported cases + This chart shows one way to do this. It visualizes the main COVID metrics relative to the peak of the last wave. The peak + of the last wave happened before the population was widely vaccinated. In this representation of the data, if confirmed + cases increase but hospitalizations and deaths increase to a lesser extent, it will mean that the many reported cases are leading to fewer severe forms of the disease, and fewer deaths. - Differences between countries and between waves may arise from factors such - as: the number of vaccine doses administered - per person; immunity from previous infections; the variants that are dominant - within the population; the demographics - of the population; and the demographics of people who have been vaccinated. - For example, countries where the elderly - and most vulnerable have been vaccinated at higher rates may have fewer severe - outcomes. + Differences between countries and between waves may arise from factors such as: the number of vaccine doses administered + per person; immunity from previous infections; the variants that are dominant within the population; the demographics + of the population; and the demographics of people who have been vaccinated. For example, countries where the elderly and + most vulnerable have been vaccinated at higher rates may have fewer severe outcomes. Our sources for these charts are: - - Germany: Robert Koch Institute + - Germany: [Robert Koch Institute](https://github.com/robert-koch-institut/) - - Israel: Government - of Israel, automated via dancarmoz - on GitHub + - Israel: [Government of Israel](https://datadashboard.health.gov.il/COVID-19/general), automated via [dancarmoz on GitHub](https://github.com/dancarmoz/israel_moh_covid_dashboard_data/) - - Spain: National Center for Epidemiology + - Spain: [National Center for Epidemiology](https://cnecovid.isciii.es/covid19/) - - United States: US - CDC and Department - of Health & Human Services + - United States: [US CDC](https://covid.cdc.gov/covid-data-tracker/#trends_dailycases) and [Department of Health & Human + Services](https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh) sources: - name: Official data collated by Our World in Data published_by: Official data collated by Our World in Data - tables: decoupling_metrics: variables: diff --git a/etl/steps/data/garden/covid/latest/ecdc.meta.yml b/etl/steps/data/garden/covid/latest/ecdc.meta.yml index 0b87318e90d..4d5ef16850f 100644 --- a/etl/steps/data/garden/covid/latest/ecdc.meta.yml +++ b/etl/steps/data/garden/covid/latest/ecdc.meta.yml @@ -1,23 +1,18 @@ dataset: title: COVID-2019 - ECDC (2020) description: >- - Raw data on confirmed cases and deaths for all countries is sourced from the - European - Centre for Disease Prevention and Control (ECDC). + Raw data on confirmed cases and deaths for all countries is sourced from the [European Centre for Disease Prevention and + Control (ECDC)](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide). - Our complete COVID-19 dataset is a collection of the COVID-19 data maintained - by Our World in Data. It - is updated daily and includes data on confirmed cases, deaths, and - testing. + Our complete COVID-19 dataset is a collection of the COVID-19 data maintained by *Our World in Data*. **It is updated + daily** and includes data on confirmed cases, deaths, and testing. - We have created a new description of all our data sources. You find it at our - GitHub repository here. + We have created a new description of all our data sources. You find it at our GitHub repository **[here](https://github.com/owid/covid-19-data/tree/master/public/data/)**. There you can download all of our data. sources: - name: European CDC – Situation Update Worldwide – Last updated {TODAY} - (London time) url: https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide published_by: European Centre for Disease Prevention and Control (ECDC) tables: @@ -96,7 +91,7 @@ tables: yearIsDay: true zeroDay: '2020-01-21' case_fatality_rate_of_covid_19__pct__only_observations_with__gte_100_cases: - title: Case fatality rate of COVID-19 (%) (Only observations with ≥100 cases) + title: "Case fatality rate of COVID-19 (%) (Only observations with ≥100 cases)" unit: '%' display: entityAnnotationsMap: |- @@ -318,7 +313,7 @@ tables: yearIsDay: true zeroDay: '2020-01-21' days_since_the_total_confirmed_cases_of_covid_19_reached_100__with_population__gte__5m: - title: Days since the total confirmed cases of COVID-19 reached 100 (with population ≥ 5M) + title: "Days since the total confirmed cases of COVID-19 reached 100 (with population ≥ 5M)" unit: '' display: includeInTable: false @@ -375,7 +370,7 @@ tables: yearIsDay: true zeroDay: '2020-01-21' has_population__gte__5m_and_had__gte_100_cases__gte_21_days_ago_and_has_testing_data: - title: Has population ≥ 5M AND had ≥100 cases ≥21 days ago AND has testing data + title: "Has population ≥ 5M AND had ≥100 cases ≥21 days ago AND has testing data" unit: '' display: yearIsDay: true diff --git a/etl/steps/data/garden/covid/latest/hospital_and_icu.meta.yml b/etl/steps/data/garden/covid/latest/hospital_and_icu.meta.yml index 39b3a43715d..3b74c2b0095 100644 --- a/etl/steps/data/garden/covid/latest/hospital_and_icu.meta.yml +++ b/etl/steps/data/garden/covid/latest/hospital_and_icu.meta.yml @@ -1,21 +1,16 @@ dataset: title: COVID-2019 - Hospital & ICU description: >- - Our hospital & ICU data is collected from official sources and collated by Our - World in Data. The complete list of country-by-country - sources is available on - GitHub. + Our hospital & ICU data is collected from official sources and collated by Our World in Data. The complete list of country-by-country + sources is available [on GitHub](https://github.com/owid/covid-19-data/blob/master/public/data/hospitalizations/locations.csv). - Our complete COVID-19 dataset is a collection of the COVID-19 data maintained - by Our World in Data. It - is updated daily and includes data on confirmed cases, deaths, and - testing. + Our complete COVID-19 dataset is a collection of the COVID-19 data maintained by *Our World in Data*. **It is updated + daily** and includes data on confirmed cases, deaths, and testing. - We have created a new description of all our data sources. You find it at our - GitHub repository here. - There you can download all of our data. + We have created a new description of all our data sources. You find it at our GitHub repository **[here](https://github.com/owid/covid-19-data/tree/master/public/data/)**. + There you can download all of our data. sources: - name: Official data collated by Our World in Data – Last updated {TODAY} url: https://github.com/owid/covid-19-data/tree/master/public/data/hospitalizations diff --git a/etl/steps/data/garden/covid/latest/john_hopkins_university.meta.yml b/etl/steps/data/garden/covid/latest/john_hopkins_university.meta.yml index 7c75545a792..793f4fd6464 100644 --- a/etl/steps/data/garden/covid/latest/john_hopkins_university.meta.yml +++ b/etl/steps/data/garden/covid/latest/john_hopkins_university.meta.yml @@ -1,42 +1,33 @@ dataset: title: COVID-19 - Johns Hopkins University description: >- - Raw data on confirmed cases and deaths for all countries is sourced from the - COVID-19 - Data Repository by the Center for Systems Science and Engineering (CSSE) at - Johns Hopkins University. + Raw data on confirmed cases and deaths for all countries is sourced from the [COVID-19 Data Repository by the Center for + Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19). - Our complete COVID-19 dataset is a collection of the COVID-19 data maintained - by Our World in Data. It - is updated daily and includes data on confirmed cases, deaths, hospitalizations, + Our complete COVID-19 dataset is a collection of the COVID-19 data maintained by **Our World in Data** + **It is updated daily** and includes data on confirmed cases, deaths, hospitalizations, and testing. - We have created a new description of all our data sources. You find it at our - GitHub repository here. + We have created a new description of all our data sources. You find it at our GitHub repository **here](https://github.com/owid/covid-19-data/tree/master/public/data** There you can download all of our data. - This data set is licensed under the Creative Commons Attribution 4.0 International - (CC BY 4.0) by Johns Hopkins University + This data set is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) by Johns Hopkins University on behalf of its Center for Systems Science in Engineering. - Attribute the data as the "COVID-19 Data Repository by the Center for Systems - Science and Engineering (CSSE) at Johns + Attribute the data as the "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University" or "JHU CSSE COVID-19 Data" for short, and the URL: https://github.com/CSSEGISandData/COVID-19. - For publications that use the data, please cite the following publication: "Dong - E, Du H, Gardner L. An interactive - web-based dashboard to track COVID-19 in real-time. Lancet Inf Dis. 20(5):533-534. - DOI: 10.1016/S1473-3099(20)30120-1" + For publications that use the data, please cite the following publication: "Dong E, Du H, Gardner L. An interactive web-based + dashboard to track COVID-19 in real-time. Lancet Inf Dis. 20(5):533-534. DOI: 10.1016/S1473-3099(20)30120-1" sources: - name: Johns Hopkins University CSSE COVID-19 Data url: https://github.com/CSSEGISandData/COVID-19 - published_by: COVID-19 Data Repository by the Center for Systems Science and Engineering - (CSSE) at Johns Hopkins University + published_by: COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University tables: john_hopkins_university: variables: @@ -107,7 +98,7 @@ tables: yearIsDay: true zeroDay: '2020-01-21' case_fatality_rate_of_covid_19__pct__only_observations_with__gte_100_cases: - title: Case fatality rate of COVID-19 (%) (Only observations with ≥100 cases) + title: "Case fatality rate of COVID-19 (%) (Only observations with ≥100 cases)" unit: '%' display: entityAnnotationsMap: '' diff --git a/etl/steps/data/garden/covid/latest/sequencing.meta.yml b/etl/steps/data/garden/covid/latest/sequencing.meta.yml index a1b74c1f4cb..1bd6f545436 100644 --- a/etl/steps/data/garden/covid/latest/sequencing.meta.yml +++ b/etl/steps/data/garden/covid/latest/sequencing.meta.yml @@ -1,33 +1,27 @@ dataset: title: COVID-19 - Sequencing description: >- - Enabled by data from + Enabled by data from [![](https://www.gisaid.org/fileadmin/gisaid/img/schild.png)](https://gisaid.org) - Our data on SARS-CoV-2 sequencing and variants is sourced from GISAID, - a global science - initiative that provides open-access to genomic data of SARS-CoV-2. We recognize - the work of the authors and laboratories - responsible for producing this data and sharing it via the GISAID initiative. + Our data on SARS-CoV-2 sequencing and variants is sourced from [GISAID](https://gisaid.org), a global science initiative + that provides open-access to genomic data of SARS-CoV-2. We recognize the work of the authors and laboratories responsible + for producing this data and sharing it via the GISAID initiative. - Khare, S., et al (2021) GISAID’s Role in Pandemic Response. China CDC Weekly, - 3(49): 1049-1051. doi: 10.46234/ccdcw2021.255 PMCID: - 8668406 + Khare, S., et al (2021) GISAID’s Role in Pandemic Response. China CDC Weekly, 3(49): 1049-1051. doi: 10.46234/ccdcw2021.255 + PMCID: 8668406 - Elbe, S. and Buckland-Merrett, G. (2017) Data, disease and diplomacy: GISAID’s - innovative contribution to global health. - Global Challenges, 1:33-46. doi:10.1002/gch2.1018 PMCID: 31565258 + Elbe, S. and Buckland-Merrett, G. (2017) Data, disease and diplomacy: GISAID’s innovative contribution to global health. + Global Challenges, 1:33-46. doi:10.1002/gch2.1018 PMCID: 31565258 - Shu, Y. and McCauley, J. (2017) GISAID: from vision to reality. EuroSurveillance, - 22(13) doi:10.2807/1560-7917.ES.2017.22.13.30494 + Shu, Y. and McCauley, J. (2017) GISAID: from vision to reality. EuroSurveillance, 22(13) doi:10.2807/1560-7917.ES.2017.22.13.30494 PMCID: PMC5388101 - We download aggregate-level data via CoVariants.org. + We download aggregate-level data via [CoVariants.org](https://covariants.org). sources: - name: GISAID, via CoVariants.org – Last updated {TODAY} url: https://www.gisaid.org/ diff --git a/etl/steps/data/garden/covid/latest/sweden.meta.yml b/etl/steps/data/garden/covid/latest/sweden.meta.yml index 265480ae046..1a74e644d8e 100644 --- a/etl/steps/data/garden/covid/latest/sweden.meta.yml +++ b/etl/steps/data/garden/covid/latest/sweden.meta.yml @@ -1,14 +1,11 @@ dataset: title: COVID-19 - Swedish Public Health Agency description: >- - This data on confirmed COVID-19 deaths is imported directly from the dataset - published by the Swedish Public Health - Agency (Folkhälsomyndigheten). + This data on confirmed COVID-19 deaths is imported directly from the dataset published by the Swedish Public Health Agency + (Folkhälsomyndigheten). - More information on this dataset and the reporting method is available in our - dedicated blog post. + More information on this dataset and the reporting method is available in [our dedicated blog post](https://ourworldindata.org/covid-sweden-death-reporting). sources: - name: Swedish Public Health Agency – Last updated {TODAY} url: https://www.folkhalsomyndigheten.se/smittskydd-beredskap/utbrott/aktuella-utbrott/covid-19/statistik-och-analyser/bekraftade-fall-i-sverige/ diff --git a/etl/steps/data/garden/covid/latest/variants.meta.yml b/etl/steps/data/garden/covid/latest/variants.meta.yml index 7b2aa00bc37..02bdae5299a 100644 --- a/etl/steps/data/garden/covid/latest/variants.meta.yml +++ b/etl/steps/data/garden/covid/latest/variants.meta.yml @@ -5,33 +5,27 @@ default_display: &default_display dataset: title: COVID-19 - Variants description: >- - Enabled by data from + Enabled by data from [![](https://www.gisaid.org/fileadmin/gisaid/img/schild.png)](https://gisaid.org) - Our data on SARS-CoV-2 sequencing and variants is sourced from GISAID, - a global science - initiative that provides open-access to genomic data of SARS-CoV-2. We recognize - the work of the authors and laboratories - responsible for producing this data and sharing it via the GISAID initiative. + Our data on SARS-CoV-2 sequencing and variants is sourced from [GISAID](https://gisaid.org), a global science initiative + that provides open-access to genomic data of SARS-CoV-2. We recognize the work of the authors and laboratories responsible + for producing this data and sharing it via the GISAID initiative. - Khare, S., et al (2021) GISAID’s Role in Pandemic Response. China CDC Weekly, - 3(49): 1049-1051. doi: 10.46234/ccdcw2021.255 PMCID: - 8668406 + Khare, S., et al (2021) GISAID’s Role in Pandemic Response. China CDC Weekly, 3(49): 1049-1051. doi: 10.46234/ccdcw2021.255 + PMCID: 8668406 - Elbe, S. and Buckland-Merrett, G. (2017) Data, disease and diplomacy: GISAID’s - innovative contribution to global health. - Global Challenges, 1:33-46. doi:10.1002/gch2.1018 PMCID: 31565258 + Elbe, S. and Buckland-Merrett, G. (2017) Data, disease and diplomacy: GISAID’s innovative contribution to global health. + Global Challenges, 1:33-46. doi:10.1002/gch2.1018 PMCID: 31565258 - Shu, Y. and McCauley, J. (2017) GISAID: from vision to reality. EuroSurveillance, - 22(13) doi:10.2807/1560-7917.ES.2017.22.13.30494 + Shu, Y. and McCauley, J. (2017) GISAID: from vision to reality. EuroSurveillance, 22(13) doi:10.2807/1560-7917.ES.2017.22.13.30494 PMCID: PMC5388101 - We download aggregate-level data via CoVariants.org. + We download aggregate-level data via [CoVariants.org](https://covariants.org). sources: - name: GISAID, via CoVariants.org – Last updated {TODAY} url: https://www.gisaid.org/ diff --git a/etl/steps/data/garden/demography/2022-12-08/population/meta.yml b/etl/steps/data/garden/demography/2022-12-08/population/meta.yml index 60a80e0adcb..8d6ea8b51f2 100644 --- a/etl/steps/data/garden/demography/2022-12-08/population/meta.yml +++ b/etl/steps/data/garden/demography/2022-12-08/population/meta.yml @@ -12,37 +12,30 @@ dataset: - Gapminder (Systema Globalis): Covers the period 1555-2008. It complements the dataset with former countries and other data points not present in the other sources. For a more detailed description, please refer to the field "source" in table "population". - - version: "2022-12-08" + version: '2022-12-08' sources: &population-sources - - name: Gapminder (2019) - published_by: Gapminder (v6) - url: https://docs.google.com/spreadsheets/d/14_suWY8fCPEXV0MH7ZQMZ-KndzMVsSsA5HdR-7WqAC0/edit#gid=501532268 - date_accessed: October 8, 2021 - - name: UN (2022) - published_by: UN, World Population Prospects (2022) - url: https://population.un.org/wpp/Download/Standard/Population/ - date_accessed: September 10, 2022 - - name: HYDE (2017) - published_by: HYDE (v3.2) - url: https://dataportaal.pbl.nl/downloads/HYDE/ - date_accessed: October 8, 2021 - # the following source contains population for former countries - # after researching where this comes from, conclusion is that - # it comes from Gapminder v3 https://www.gapminder.org/data/documentation/gd003/ - # and is downloadable via button labeled with text: - # "» Download Excel-file with data, including interpolations & detailed meta-data (xlsx)" - - name: Gapminder (Systema Globalis) - published_by: Gapminder (Systema Globalis) - url: https://github.com/open-numbers/ddf--gapminder--systema_globalis - date_accessed: December 12, 2022 + - name: Gapminder (2019) + published_by: Gapminder (v6) + url: https://docs.google.com/spreadsheets/d/14_suWY8fCPEXV0MH7ZQMZ-KndzMVsSsA5HdR-7WqAC0/edit#gid=501532268 + date_accessed: October 8, 2021 + - name: UN (2022) + published_by: UN, World Population Prospects (2022) + url: https://population.un.org/wpp/Download/Standard/Population/ + date_accessed: September 10, 2022 + - name: HYDE (2017) + published_by: HYDE (v3.2) + url: https://dataportaal.pbl.nl/downloads/HYDE/ + date_accessed: October 8, 2021 + - name: Gapminder (Systema Globalis) + published_by: Gapminder (Systema Globalis) + url: https://github.com/open-numbers/ddf--gapminder--systema_globalis + date_accessed: December 12, 2022 tables: population: title: Population (various sources) description: | Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on three key sources: HYDE, Gapminder, and the UN World Population Prospects. - You can find more information on these sources and how our time series is constructed on this page: What sources do we rely on for population estimates? - + You can find more information on these sources and how our time series is constructed on this page: [What sources do we rely on for population estimates?](https://ourworldindata.org/population-sources) variables: population: title: Population @@ -67,8 +60,8 @@ tables: * 1800-1949: Historical estimates by Gapminder. Includes some datapoints from HYDE (v3.2) and Gapminder (Systema Globalis). * 1950-2021: Population records by the United Nations - Population Division (2022). Includes some datapoints from HYDE (v3.2), Gapminder (Systema Globalis) and Gapminder (v6). * 2022-2100: Projections based on Medium variant by the United Nations - Population Division (2022). - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: name: Share of world population includeInTable: true @@ -77,4 +70,4 @@ tables: title: Source description: | Name of the source for a specific data point. The name includes a short name for the source and a link. - unit: "" + unit: '' diff --git a/etl/steps/data/garden/demography/2023-02-03/life_expectancy.meta.yml b/etl/steps/data/garden/demography/2023-02-03/life_expectancy.meta.yml index aaf3a8fcf32..cd736a211cf 100644 --- a/etl/steps/data/garden/demography/2023-02-03/life_expectancy.meta.yml +++ b/etl/steps/data/garden/demography/2023-02-03/life_expectancy.meta.yml @@ -55,257 +55,173 @@ dataset: For continents, we use UN's definitions for values after 1950 and Riley (2005) definitions for values prior to 1950. Note that Riley reports "Americas", while the UN reports "Northern America" and "Latin America and the Caribbean" separately. - SOURCES + **SOURCES** - World Population Prospects - UN (2022) + **World Population Prospects - UN (2022)** World Population Prospects 2022 is the 27th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. More details at https://population.un.org/wpp/Publications/. - Life Tables - Human Mortality Database (2022-11-04) + **Life Tables - Human Mortality Database (2022-11-04)** To facilitate rapid downloads, the database has been organized into zipped data files. Two series of files are intended for different purposes and for different users. For users who want to obtain all available data for an individual country or for all countries, the zipped data files labeled "By country" are recommended. The file organization follows internal practices and is not particularly user-friendly, but all publicly-available HMD data are included in this set.For users who only want information of a given kind for all countries, the files "By statistic" are recommended. In this case the file organization is simpler, but only certain parts of the database (i.e., items labeled "Complete Data Series" on country pages) are available in this format. More details can be found at https://www.mortality.org/Data/ExplanatoryNotes. - Life Expectancy at Birth (Total) - Zijdeman et al. (2015) + **Life Expectancy at Birth (Total) - Zijdeman et al. (2015)** This dataset provides Period Life Expectancy at birth per country and year. The overall aim of the dataset is to cover the entire world for the period 1500-2000. The current version (version 2) was build as part of the OECD "How was life" project. The dataset has nearly global coverage for the post 1950 period, while pre 1950 the coverage decreases the more historic the time period. Depending on sources, the data are annual estimates, 5 yearly or decadel estimates The sources used are: - - UN World Population Project. - - http://www.mortality.org. - - http://www.gapminder.org. - - http://stats.oecd.org. - - Montevideo-Oxford Latin America Economic History Database. - - http://www.ons.gov.uk/ons/datasets-and-tables/index.html. - - http://www.abs.gov.au/ausstats/abs@.nsf/web+pages/statistics?opendocument#from-banner=LN. + - [UN World Population Project](http://esa.un.org/wpp/). + - [Human Mortality Database](http://www.mortality.org). + - [Gapminder](http://www.gapminder.org). + - [OECD](http://stats.oecd.org). + - [Montevideo-Oxford Latin America Economic History Database](http://www.lac.ox.ac.uk/moxlad-database). + - [ONS](http://www.ons.gov.uk/ons/datasets-and-tables/index.html). + - [Australian Bureau of Statistics](http://www.abs.gov.au/ausstats/abs@.nsf/web+pages/statistics?opendocument#from-banner=LN). - Kannisto, V., Nieminen, M. & Turpeinen, O. (1999). Finnish Life Tables since 1751, Demographic Research, 1(1), DOI: 10.4054/DemRes.1999.1.1 Link to paper can be found at https://clio-infra.eu/docs/Total_life_expectancy.docx. - Estimates of Regional and Global Life Expectancy, 1800-2001 - Riley (2005) + **Estimates of Regional and Global Life Expectancy, 1800-2001 - Riley (2005)** Historians and demographers have gone to considerable trouble to reconstruct life expectancy in the past in individual countries. This overview collects information from a large body of that work and links estimates for historical populations to those provided by the United Nations, the World Bank, and other sources for 1950-2001. The result is a picture of regional and global life expectancy at birth for selected years from 1800 to 2001. The bibliography of more than 700 sources is published separately on the web. - version: "2022-11-30" + version: '2022-11-30' licenses: - - *un_license - - *hmd_license - - *zijdeman_license - - *riley_license + - *un_license + - *hmd_license + - *zijdeman_license + - *riley_license sources: - - *un_source - - *hmd_source - - *zijdeman_source - - *riley_source + - *un_source + - *hmd_source + - *zijdeman_source + - *riley_source tables: historical: title: Life Expectancy (various sources) - Historical variables: life_expectancy_0_hist: title: Life expectancy at birth (historical) - description: - "The average number of years that a newborn could expect to live, - if he or she were to pass through life exposed to the sex- and age-specific - death rates prevailing at the time of his or her birth, for a specific year, - in a given country, territory, or geographic area. - - - Definition from the WHO. - - " + description: "The average number of years that a newborn could expect to live, if he or she were to pass through life + exposed to the sex- and age-specific death rates prevailing at the time of his or her birth, for a specific year, + in a given country, territory, or geographic area.\n\nDefinition from the WHO.\n" unit: years short_unit: years sources: - - *un_source - - *zijdeman_source - - *riley_source + - *un_source + - *zijdeman_source + - *riley_source life_expectancy_15_hist: title: Life expectancy at 15 (historical) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 15 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 15 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source - - *hmd_source + - *un_source + - *hmd_source life_expectancy_65_hist: title: Life expectancy at 65 (historical) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 65 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 65 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source - - *hmd_source + - *un_source + - *hmd_source life_expectancy_80_hist: title: Life expectancy at 80 (historical) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 80 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 80 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source - - *hmd_source + - *un_source + - *hmd_source life_expectancy: title: Life Expectancy (various sources) variables: life_expectancy_0: title: Life expectancy at birth - description: - "The average number of years that a newborn could expect to live, - if he or she were to pass through life exposed to the sex- and age-specific - death rates prevailing at the time of his or her birth, for a specific year, - in a given country, territory, or geographic area. - - - Definition from the WHO. - - " + description: "The average number of years that a newborn could expect to live, if he or she were to pass through life + exposed to the sex- and age-specific death rates prevailing at the time of his or her birth, for a specific year, + in a given country, territory, or geographic area.\n\nDefinition from the WHO.\n" unit: years short_unit: years sources: - - *un_source - - *zijdeman_source - - *riley_source + - *un_source + - *zijdeman_source + - *riley_source life_expectancy_15: title: Life expectancy at 15 - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 15 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 15 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source - - *hmd_source + - *un_source + - *hmd_source life_expectancy_65: title: Life expectancy at 65 - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 65 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 65 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source - - *hmd_source + - *un_source + - *hmd_source life_expectancy_80: title: Life expectancy at 80 - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 80 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 80 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source - - *hmd_source + - *un_source + - *hmd_source projection: title: Life Expectancy (various sources) - Projection variables: life_expectancy_0_proj: title: Life expectancy at birth (projection) - description: - "The average number of years that a newborn could expect to live, - if he or she were to pass through life exposed to the sex- and age-specific - death rates prevailing at the time of his or her birth, for a specific year, - in a given country, territory, or geographic area. - - - Definition from the WHO. - - " + description: "The average number of years that a newborn could expect to live, if he or she were to pass through life + exposed to the sex- and age-specific death rates prevailing at the time of his or her birth, for a specific year, + in a given country, territory, or geographic area.\n\nDefinition from the WHO.\n" unit: years short_unit: years sources: - - *un_source + - *un_source life_expectancy_15_proj: title: Life expectancy at 15 (projection) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 15 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 15 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source + - *un_source life_expectancy_65_proj: title: Life expectancy at 65 (projection) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 65 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 65 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source - - *hmd_source + - *un_source + - *hmd_source life_expectancy_80_proj: title: Life expectancy at 80 (projection) - description: - "The average number of remaining years of life expected by a - hypothetical cohort of individuals who already reached age 80 and would - be subject during the remainder of their lives to the mortality rates of - a given period. It is expressed as years. - - - Definition from the UN. - - " + description: "The average number of remaining years of life expected by a hypothetical cohort of individuals who already + reached age 80 and would be subject during the remainder of their lives to the mortality rates of a given period. + It is expressed as years.\n\nDefinition from the UN.\n" unit: years short_unit: years sources: - - *un_source + - *un_source diff --git a/etl/steps/data/garden/demography/2023-03-31/population/meta.yml b/etl/steps/data/garden/demography/2023-03-31/population/meta.yml index 38b3a2cdd76..565d9764627 100644 --- a/etl/steps/data/garden/demography/2023-03-31/population/meta.yml +++ b/etl/steps/data/garden/demography/2023-03-31/population/meta.yml @@ -6,69 +6,71 @@ dataset: • UN WPP (2022): Covers the period 1950-2100. Future projections are based on the Medium variant. - • Gapminder (v7): Mostly covers the period 1800-1949. In addition, it complements the dataset with population data for the - "Vatican" until 2100 (it is missing in UN WPP's estimates). + • Gapminder (v7): Mostly covers the period 1800-1949. In addition, it complements the dataset with population data for + the "Vatican" until 2100 (it is missing in UN WPP's estimates). - • HYDE (v3.2): Mostly covers the period 10,000 BCE - 1799. In addition, it complements the dataset with population for some countries - outside of this year period. E.g. it provides data for "Svalbard and Jan Mayen" (until 2017) and "Netherlands Antilles" (until 2010). + • HYDE (v3.2): Mostly covers the period 10,000 BCE - 1799. In addition, it complements the dataset with population for + some countries outside of this year period. E.g. it provides data for "Svalbard and Jan Mayen" (until 2017) and "Netherlands + Antilles" (until 2010). - • Gapminder (v7): Mostly covers the period 1800-1949. In addition, it complements the dataset with population data for the "Vatican" until 2100 (it is missing in UN WPP's estimates). + • Gapminder (v7): Mostly covers the period 1800-1949. In addition, it complements the dataset with population data for + the "Vatican" until 2100 (it is missing in UN WPP's estimates). • HYDE (v3.2): Mostly covers the period 10,000 BCE - 1799. In addition, it complements the dataset with population for - some countries outside of this year period. E.g. it provides data for "Svalbard and Jan Mayen" (until 2017) and "Netherlands Antilles" (until 2010). + some countries outside of this year period. E.g. it provides data for "Svalbard and Jan Mayen" (until 2017) and "Netherlands + Antilles" (until 2010). - • Gapminder (Systema Globalis): Covers the period 1555-2008. It complements the dataset with former countries and other data points not present in the other sources. + • Gapminder (Systema Globalis): Covers the period 1555-2008. It complements the dataset with former countries and other + data points not present in the other sources. sources: &population-sources - - name: Gapminder (2022) - published_by: Gapminder (v7) - url: https://www.gapminder.org/data/documentation/gd003/ - date_accessed: 2023-03-31 - - name: UN (2022) - published_by: United Nations, World Population Prospects (2022) - url: https://population.un.org/wpp/Download/Standard/Population/ - date_accessed: 2022-09-10 - - name: HYDE (2017) - published_by: HYDE (v3.2) - url: https://dataportaal.pbl.nl/downloads/HYDE/ - date_accessed: 2021-10-08 - # the following source contains population for former countries - # after researching where this comes from, conclusion is that - # it comes from Gapminder v3 https://www.gapminder.org/data/documentation/gd003/ - # and is downloadable via button labeled with text: - # "» Download Excel-file with data, including interpolations & detailed meta-data (xlsx)" - - name: Gapminder (Systema Globalis) - published_by: Gapminder (Systema Globalis) - url: https://github.com/open-numbers/ddf--gapminder--systema_globalis - date_accessed: 2022-12-12 + - name: Gapminder (2022) + published_by: Gapminder (v7) + url: https://www.gapminder.org/data/documentation/gd003/ + date_accessed: 2023-03-31 + - name: UN (2022) + published_by: United Nations, World Population Prospects (2022) + url: https://population.un.org/wpp/Download/Standard/Population/ + date_accessed: 2022-09-10 + - name: HYDE (2017) + published_by: HYDE (v3.2) + url: https://dataportaal.pbl.nl/downloads/HYDE/ + date_accessed: 2021-10-08 + - name: Gapminder (Systema Globalis) + published_by: Gapminder (Systema Globalis) + url: https://github.com/open-numbers/ddf--gapminder--systema_globalis + date_accessed: 2022-12-12 licenses: - - name: Creative Commons BY 4.0 - url: https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing - - name: CC BY 3.0 IGO - url: http://creativecommons.org/licenses/by/3.0/igo/ - - name: CC BY 3.0 - url: https://dataportaal.pbl.nl/downloads/HYDE/HYDE3.2/readme_release_HYDE3.2.1.txt - - name: Creative Commons BY 4.0 - url: https://creativecommons.org/licenses/by/4.0/ + - name: Creative Commons BY 4.0 + url: https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing + - name: CC BY 3.0 IGO + url: http://creativecommons.org/licenses/by/3.0/igo/ + - name: CC BY 3.0 + url: https://dataportaal.pbl.nl/downloads/HYDE/HYDE3.2/readme_release_HYDE3.2.1.txt + - name: Creative Commons BY 4.0 + url: https://creativecommons.org/licenses/by/4.0/ tables: population: title: Population (various sources) description: >- - Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on three key sources: HYDE, Gapminder, and the UN World Population Prospects. - - You can find more information on these sources and how our time series is constructed on this page: What sources do we rely on for population estimates? + Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based + on three key sources: HYDE, Gapminder, and the UN World Population Prospects. + You can find more information on these sources and how our time series is constructed on this page: [What sources do we rely on for population estimates?](https://ourworldindata.org/population-sources) variables: population: title: Population description: >- - Population by country, available from 10,000 BCE to 2100 based on Gapminder data, HYDE, and UN Population Division (2022) estimates. + Population by country, available from 10,000 BCE to 2100 based on Gapminder data, HYDE, and UN Population Division + (2022) estimates. • 10,000 BCE - 1799: Historical estimates by HYDE (v3.2). Includes some datapoints from Gapminder (Systema Globalis). - • 1800-1949: Historical estimates by Gapminder. Includes some datapoints from HYDE (v3.2) and Gapminder (Systema Globalis). + • 1800-1949: Historical estimates by Gapminder. Includes some datapoints from HYDE (v3.2) and Gapminder (Systema + Globalis). - • 1950-2021: Population records by the UN World Population Prospects (2022 revision). Includes some datapoints from HYDE (v3.2), Gapminder (Systema Globalis) and Gapminder (v7). + • 1950-2021: Population records by the UN World Population Prospects (2022 revision). Includes some datapoints from + HYDE (v3.2), Gapminder (Systema Globalis) and Gapminder (v7). • 2022-2100: Projections based on Medium variant by the UN World Population Prospects (2022 revision). unit: persons @@ -80,18 +82,21 @@ tables: world_pop_share: title: Share of world population description: >- - Share of the world's population by country, available from 10,000 BCE to 2100 based on Gapminder data, HYDE, and UN Population Division (2022) estimates. + Share of the world's population by country, available from 10,000 BCE to 2100 based on Gapminder data, HYDE, and + UN Population Division (2022) estimates. • 10,000 BCE - 1799: Historical estimates by HYDE (v3.2). Includes some datapoints Gapminder (Systema Globalis). - • 1800-1949: Historical estimates by Gapminder. Includes some datapoints from HYDE (v3.2) and Gapminder (Systema Globalis). + • 1800-1949: Historical estimates by Gapminder. Includes some datapoints from HYDE (v3.2) and Gapminder (Systema + Globalis). - • 1950-2021: Population records by the UN World Population Prospects (2022 revision). Includes some datapoints from HYDE (v3.2), Gapminder (Systema Globalis) and Gapminder (v7). + • 1950-2021: Population records by the UN World Population Prospects (2022 revision). Includes some datapoints from + HYDE (v3.2), Gapminder (Systema Globalis) and Gapminder (v7). • 2022-2100: Projections based on Medium variant by the UN World Population Prospects (2022 revision). - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: name: Share of world population includeInTable: true @@ -100,4 +105,4 @@ tables: title: Source description: | Name of the source for a specific data point. The name includes a short name for the source and a link. - unit: "" + unit: '' diff --git a/etl/steps/data/garden/ember/2022-08-01/global_electricity_review.meta.yml b/etl/steps/data/garden/ember/2022-08-01/global_electricity_review.meta.yml index f3e2823c3aa..84113c3e653 100644 --- a/etl/steps/data/garden/ember/2022-08-01/global_electricity_review.meta.yml +++ b/etl/steps/data/garden/ember/2022-08-01/global_electricity_review.meta.yml @@ -4,20 +4,19 @@ dataset: title: Global Electricity Review (Ember, 2022) short_name: global_electricity_review description: | - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: + * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "Middle East (Ember)": Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates and Yemen. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on Ember's Global Electricity Review (2022). - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - + - name: Our World in Data based on Ember's Global Electricity Review (2022). + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ tables: capacity: variables: @@ -133,38 +132,38 @@ tables: variables: clean__pct: title: Clean (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Clean fossil__pct: title: Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil gas_and_other_fossil__pct: title: Gas and Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas and Other Fossil hydro__bioenergy_and_other_renewables__pct: title: Hydro, Bioenergy and Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro, Bioenergy and Other Renewables renewables__pct: title: Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables wind_and_solar__pct: title: Wind and Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind and Solar clean__twh: @@ -205,56 +204,56 @@ tables: name: Wind and Solar bioenergy__pct: title: Bioenergy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy coal__pct: title: Coal (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal gas__pct: title: Gas (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro__pct: title: Hydro (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydro nuclear__pct: title: Nuclear (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear other_fossil__pct: title: Other Fossil (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Fossil other_renewables__pct: title: Other Renewables (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other Renewables solar__pct: title: Solar (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar wind__pct: title: Wind (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind bioenergy__twh: diff --git a/etl/steps/data/garden/emdat/2022-11-24/natural_disasters.meta.yml b/etl/steps/data/garden/emdat/2022-11-24/natural_disasters.meta.yml index 3c5e287fdba..2a62358c499 100644 --- a/etl/steps/data/garden/emdat/2022-11-24/natural_disasters.meta.yml +++ b/etl/steps/data/garden/emdat/2022-11-24/natural_disasters.meta.yml @@ -1,78 +1,76 @@ all_sources: - - emdat: &source-emdat - name: EM-DAT, CRED / UCLouvain, Brussels, Belgium - url: https://emdat.be/ - date_accessed: '2022-11-27' - publication_date: '2022-11-24' - publication_year: 2022 - description: &description-emdat | - EM-DAT data includes all categories classified as "natural disasters" (distinguished from technological disasters, such as oil spills and industrial accidents). This includes those from drought, earthquakes, extreme temperatures, extreme weather, floods, fogs, glacial lake outbursts, landslide, dry mass movements, volcanic activity, and wildfires. +- emdat: &source-emdat + name: EM-DAT, CRED / UCLouvain, Brussels, Belgium + url: https://emdat.be/ + date_accessed: '2022-11-27' + publication_date: '2022-11-24' + publication_year: 2022 + description: &description-emdat | + EM-DAT data includes all categories classified as "natural disasters" (distinguished from technological disasters, such as oil spills and industrial accidents). This includes those from drought, earthquakes, extreme temperatures, extreme weather, floods, fogs, glacial lake outbursts, landslide, dry mass movements, volcanic activity, and wildfires. - Disaster-related deaths from EM-DAT have been normalized by Our World in Data to global population size based on different sources. This provides data in terms of cases per 100,000 people. + Disaster-related deaths from EM-DAT have been normalized by Our World in Data to global population size based on [different sources](https://ourworldindata.org/population-sources). This provides data in terms of cases per 100,000 people. - Our World in Data has also calculated economic damage metrics adjusted for gross domestic product (GDP), using GDP data from the World Bank's World Development Indicators. + Our World in Data has also calculated economic damage metrics adjusted for gross domestic product (GDP), using GDP data from [the World Bank's World Development Indicators](http://data.worldbank.org/data-catalog/world-development-indicators). - Latest update: 2022-12-06. - This dataset is updated regularly. On Our World in Data, given that we only show yearly (or decadal) data, we will update this dataset on a yearly basis. At the link above you can directly access the source page and see the latest available data. + Latest update: 2022-12-06. + This dataset is updated regularly. On Our World in Data, given that we only show yearly (or decadal) data, we will update this dataset on a yearly basis. At the link above you can directly access the source page and see the latest available data. - EM-DAT defines the following variables as: + EM-DAT defines the following variables as: - + Affected: People requiring immediate assistance during a period of emergency, i.e. requiring basic survival needs such as food, water, shelter, sanitation and immediate medical assistance. + + Affected: People requiring immediate assistance during a period of emergency, i.e. requiring basic survival needs such as food, water, shelter, sanitation and immediate medical assistance. - + Injured: People suffering from physical injuries, trauma or an illness requiring immediate medical assistance as a direct result of a disaster. + + Injured: People suffering from physical injuries, trauma or an illness requiring immediate medical assistance as a direct result of a disaster. - + Homeless: Number of people whose house is destroyed or heavily damaged and therefore need shelter after an event. + + Homeless: Number of people whose house is destroyed or heavily damaged and therefore need shelter after an event. - + Total affected: In EM-DAT, it is the sum of the injured, affected and left homeless after a disaster. + + Total affected: In EM-DAT, it is the sum of the injured, affected and left homeless after a disaster. - + Estimated economic damage: The amount of damage to property, crops, and livestock. In EM-DAT estimated damage are given in US$ ('000). For each disaster, the registered figure corresponds to the damage value at the moment of the event, i.e. the figures are shown true to the year of the event. + + Estimated economic damage: The amount of damage to property, crops, and livestock. In EM-DAT estimated damage are given in US$ ('000). For each disaster, the registered figure corresponds to the damage value at the moment of the event, i.e. the figures are shown true to the year of the event. - + Total deaths: In EM-DAT, it is the sum of deaths and missing. + + Total deaths: In EM-DAT, it is the sum of deaths and missing. - EM-DAT defines the following types of disasters as: + EM-DAT defines the following types of disasters as: - + Drought: An extended period of unusually low precipitation that produces a shortage of water for people, animals and plants. Drought is different from most other hazards in that it develops slowly, sometimes even over years, and its onset is generally difficult to detect. Drought is not solely a physical phenomenon because its impacts can be exacerbated by human activities and water supply demands. Drought is therefore often defined both conceptually and operationally. Operational definitions of drought, meaning the degree of precipitation reduction that constitutes a drought, vary by locality, climate and environmental sector. + + Drought: An extended period of unusually low precipitation that produces a shortage of water for people, animals and plants. Drought is different from most other hazards in that it develops slowly, sometimes even over years, and its onset is generally difficult to detect. Drought is not solely a physical phenomenon because its impacts can be exacerbated by human activities and water supply demands. Drought is therefore often defined both conceptually and operationally. Operational definitions of drought, meaning the degree of precipitation reduction that constitutes a drought, vary by locality, climate and environmental sector. - + Earthquake: Sudden movement of a block of the Earth's crust along a geological fault and associated ground shaking. + + Earthquake: Sudden movement of a block of the Earth's crust along a geological fault and associated ground shaking. - + Extreme temperature: Extreme temperature. + + Extreme temperature: Extreme temperature. - + Flood: A general term for the overflow of water from a stream channel onto normally dry land in the floodplain (riverine flooding), higher-than-normal levels along the coast and in lakes or reservoirs (coastal flooding) as well as ponding of water at or near the point where the rain fell (flash floods). + + Flood: A general term for the overflow of water from a stream channel onto normally dry land in the floodplain (riverine flooding), higher-than-normal levels along the coast and in lakes or reservoirs (coastal flooding) as well as ponding of water at or near the point where the rain fell (flash floods). - + Fog: Water droplets that are suspended in the air near the Earth's surface. Fog is simply a cloud that is in contact with the ground. + + Fog: Water droplets that are suspended in the air near the Earth's surface. Fog is simply a cloud that is in contact with the ground. - + Glacial lake outburst: A flood that occurs when water dammed by a glacier or moraine is suddenly released. Glacial lakes can be at the front of the glacier (marginal lake) or below the ice sheet (sub-glacial lake). + + Glacial lake outburst: A flood that occurs when water dammed by a glacier or moraine is suddenly released. Glacial lakes can be at the front of the glacier (marginal lake) or below the ice sheet (sub-glacial lake). - + Landslide: Any kind of moderate to rapid soil movement incl. lahar, mudslide, debris flow. A landslide is the movement of soil or rock controlled by gravity and the speed of the movement usually ranges between slow and rapid, but not very slow. It can be superficial or deep, but the materials have to make up a mass that is a portion of the slope or the slope itself. The movement has to be downward and outward with a free face. + + Landslide: Any kind of moderate to rapid soil movement incl. lahar, mudslide, debris flow. A landslide is the movement of soil or rock controlled by gravity and the speed of the movement usually ranges between slow and rapid, but not very slow. It can be superficial or deep, but the materials have to make up a mass that is a portion of the slope or the slope itself. The movement has to be downward and outward with a free face. - + Mass movement: Any type of downslope movement of earth materials. + + Mass movement: Any type of downslope movement of earth materials. - + Extreme weather: Storm. + + Extreme weather: Storm. - + Volcanic activity: A type of volcanic event near an opening/vent in the Earth's surface including volcanic eruptions of lava, ash, hot vapour, gas, and pyroclastic material. + + Volcanic activity: A type of volcanic event near an opening/vent in the Earth's surface including volcanic eruptions of lava, ash, hot vapour, gas, and pyroclastic material. - + Wildfire: Any uncontrolled and non-prescribed combustion or burning of plants in a natural setting such as a forest, grassland, brush land or tundra, which consumes the natural fuels and spreads based on environmental conditions (e.g., wind, topography). Wildfires can be triggered by lightning or human actions. + + Wildfire: Any uncontrolled and non-prescribed combustion or burning of plants in a natural setting such as a forest, grassland, brush land or tundra, which consumes the natural fuels and spreads based on environmental conditions (e.g., wind, topography). Wildfires can be triggered by lightning or human actions. +- wdi: &source-wdi + name: World Development Indicators - World Bank + url: https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators + date_accessed: '2022-05-26' + publication_year: 2022 + description: &description-wdi | + The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates. +- population: &source-population + name: Population (Gapminder, HYDE & UN) + description: &description-population | + Population by country, available from 10,000 BCE to 2100, is based on Gapminder data, HYDE, and UN Population Division (2022) estimates. - - wdi: &source-wdi - name: World Development Indicators - World Bank - url: https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators - date_accessed: '2022-05-26' - publication_year: 2022 - description: &description-wdi | - The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates. - - population: &source-population - name: Population (Gapminder, HYDE & UN) - description: &description-population | - Population by country, available from 10,000 BCE to 2100, is based on Gapminder data, HYDE, and UN Population Division (2022) estimates. + + 10,000 BCE - 1799: Historical estimates by [HYDE (v3.2)](https://dataportaal.pbl.nl/downloads/HYDE/). - + 10,000 BCE - 1799: Historical estimates by HYDE (v3.2). + + 1800-1949: Historical estimates by [Gapminder (v6)](https://www.gapminder.org/data/documentation/gd003/). - + 1800-1949: Historical estimates by Gapminder (v6). - - + 1950-2021: Population records by the United Nations - Population Division (2022). - - + 2022-2100: Projections based on Medium variant by the United Nations - Population Division (2022). + + 1950-2021: Population records by [the United Nations - Population Division (2022)](https://population.un.org/wpp/Download/Standard/Population/). + + 2022-2100: Projections based on Medium variant by [the United Nations - Population Division (2022)](https://population.un.org/wpp/Download/Standard/Population/). dataset: namespace: emdat short_name: natural_disasters diff --git a/etl/steps/data/garden/emissions/2023-07-10/owid_co2.meta.yml b/etl/steps/data/garden/emissions/2023-07-10/owid_co2.meta.yml index ee1d1cfd50c..5d894bf3eb1 100644 --- a/etl/steps/data/garden/emissions/2023-07-10/owid_co2.meta.yml +++ b/etl/steps/data/garden/emissions/2023-07-10/owid_co2.meta.yml @@ -3,7 +3,7 @@ dataset: description: | OWID CO2 dataset. - This dataset will be loaded by the co2-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the co2-data repository](https://github.com/owid/co2-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' original metadata. diff --git a/etl/steps/data/garden/energy/2022-08-03/electricity_mix.meta.yml b/etl/steps/data/garden/energy/2022-08-03/electricity_mix.meta.yml index a73dec8731f..dadb931b65c 100644 --- a/etl/steps/data/garden/energy/2022-08-03/electricity_mix.meta.yml +++ b/etl/steps/data/garden/energy/2022-08-03/electricity_mix.meta.yml @@ -5,9 +5,9 @@ dataset: short_name: electricity_mix description: | Data is compiled by Our World in Data based on three main sources: - – BP Statistical Review of World Energy. - – Ember Global Electricity Review (2022). - – Ember European Electricity Review (2022). + – [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + – [Ember Global Electricity Review (2022)](https://ember-climate.org/data-catalogue/yearly-electricity-data/). + – [Ember European Electricity Review (2022)](https://ember-climate.org/insights/research/european-electricity-review-2022/). Ember compile their global dataset from various sources including: – Eurostat: Annual European generation and import data, and monthly data in some cases where better sources are not available. @@ -18,16 +18,16 @@ dataset: – IRENA: Annual global capacity data for all non-fossil fuel types, and for Other Fossil where available. – WRI: Annual global capacity data for Other Fossil where other sources are not available. – European carbon intensities rely on data from the European Environment Agency (EEA). - – A complete list of data sources for each individual country in Ember's Global Electricity Review can be found here. - – A complete list of data sources for each individual country in Ember's European Electricity Review can be found here. + – A complete list of data sources for each individual country in Ember's Global Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/03/GER22-Methodology.pdf). + – A complete list of data sources for each individual country in Ember's European Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/02/EER-Methodology.pdf). We rely on BP as the primary source of electricity consumption data for two reasons. BP provides primary energy (not just electricity) consumption data, and it provides a longer time-series (dating back to 1965) than Ember (which only dates back to 1990). However, BP does not provide data for all countries. So, where data from BP is available for a given country and year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. Our World in Data has converted absolute electricity production by source to the share in the mix by dividing each by total electricity production. - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html#accordion_Regional%20definitions), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -53,33 +53,29 @@ dataset: * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "Middle East (Ember)": Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates and Yemen. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Our World in Data based on Ember's Global Electricity Review (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Our World in Data based on Ember's European Electricity Review (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Our World in Data based on Ember's Global Electricity Review (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Our World in Data based on Ember's European Electricity Review (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: electricity_mix: variables: @@ -91,14 +87,14 @@ tables: name: Bioenergy bioenergy_share_of_electricity__pct: title: Bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy co2_intensity__gco2_kwh: title: Carbon intensity of electricity (gCO2/kWh) - short_unit: gCO₂ - unit: grams of CO₂ equivalent per kilowatt-hour + short_unit: "gCO₂" + unit: "grams of CO₂ equivalent per kilowatt-hour" display: name: Carbon intensity of electricity per kilowatt-hour coal_generation__twh: @@ -109,8 +105,8 @@ tables: name: Coal coal_share_of_electricity__pct: title: Coal (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal fossil_generation__twh: @@ -121,8 +117,8 @@ tables: name: Fossil fuels fossil_share_of_electricity__pct: title: Fossil fuels (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil fuels gas_generation__twh: @@ -133,8 +129,8 @@ tables: name: Gas gas_share_of_electricity__pct: title: Gas (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro_generation__twh: @@ -145,8 +141,8 @@ tables: name: Hydropower hydro_share_of_electricity__pct: title: Hydro (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydropower low_carbon_generation__twh: @@ -157,14 +153,14 @@ tables: name: Low-carbon electricity low_carbon_share_of_electricity__pct: title: Low-carbon electricity (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Share of electricity from low-carbon sources net_imports_share_of_demand__pct: title: Net electricity imports as a share of demand (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Net electricity imports as a share of demand nuclear_generation__twh: @@ -175,8 +171,8 @@ tables: name: Nuclear nuclear_share_of_electricity__pct: title: Nuclear (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear oil_generation__twh: @@ -187,8 +183,8 @@ tables: name: Oil oil_share_of_electricity__pct: title: Oil (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Oil other_renewables_excluding_bioenergy_generation__twh: @@ -199,8 +195,8 @@ tables: name: Other renewables, excluding bioenergy other_renewables_excluding_bioenergy_share_of_electricity__pct: title: Other renewables excluding bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, excluding bioenergy other_renewables_including_bioenergy_generation__twh: @@ -211,8 +207,8 @@ tables: name: Other renewables, including bioenergy other_renewables_including_bioenergy_share_of_electricity__pct: title: Other renewables including bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, including bioenergy per_capita_bioenergy_generation__kwh: @@ -333,8 +329,8 @@ tables: name: Renewables renewable_share_of_electricity__pct: title: Renewables (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables numDecimalPlaces: 2 @@ -346,8 +342,8 @@ tables: name: Solar solar_share_of_electricity__pct: title: Solar (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar total_demand__twh: @@ -358,8 +354,8 @@ tables: name: Electricity demand total_electricity_share_of_primary_energy__pct: title: Electricity as share of primary energy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Electricity as share of primary energy total_emissions__mtco2: @@ -388,7 +384,7 @@ tables: name: Wind wind_share_of_electricity__pct: title: Wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind diff --git a/etl/steps/data/garden/energy/2022-08-05/owid_energy.meta.yml b/etl/steps/data/garden/energy/2022-08-05/owid_energy.meta.yml index d9ca64de82f..b8a24d32d73 100644 --- a/etl/steps/data/garden/energy/2022-08-05/owid_energy.meta.yml +++ b/etl/steps/data/garden/energy/2022-08-05/owid_energy.meta.yml @@ -6,7 +6,7 @@ dataset: description: | OWID Energy dataset. - This dataset will be loaded by the energy-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the energy-data repository](https://github.com/owid/energy-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' metadata and the content of owid_energy_variable_mapping.csv. diff --git a/etl/steps/data/garden/energy/2022-09-22/uk_historical_electricity.meta.yml b/etl/steps/data/garden/energy/2022-09-22/uk_historical_electricity.meta.yml index 271155c022e..4220084d283 100644 --- a/etl/steps/data/garden/energy/2022-09-22/uk_historical_electricity.meta.yml +++ b/etl/steps/data/garden/energy/2022-09-22/uk_historical_electricity.meta.yml @@ -4,33 +4,28 @@ dataset: title: UK historical electricity short_name: uk_historical_electricity description: | - All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy. + All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from [the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy](https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes). - All other data is sourced from the BP's Statistical Review of World Energy and Ember Global Electricity Review. Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. + All other data is sourced from the [BP's Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [Ember Global Electricity Review](https://ember-climate.org/insights/research/global-electricity-review-2022/). Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. sources: - - - name: Digest of UK Energy Statistics - published_by: UK's Department for Business, Energy & Industrial Strategy - date_accessed: 2022-09-21 - url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data - - - name: BP Statistical Review of World Energy - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Ember's Global Electricity Review - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Ember's European Electricity Review - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Digest of UK Energy Statistics + published_by: UK's Department for Business, Energy & Industrial Strategy + date_accessed: 2022-09-21 + url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data + - name: BP Statistical Review of World Energy + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Ember's Global Electricity Review + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Ember's European Electricity Review + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: uk_historical_electricity: variables: diff --git a/etl/steps/data/garden/energy/2022-12-12/electricity_mix.meta.yml b/etl/steps/data/garden/energy/2022-12-12/electricity_mix.meta.yml index f07b1cdf169..6ae0f8fbbc7 100644 --- a/etl/steps/data/garden/energy/2022-12-12/electricity_mix.meta.yml +++ b/etl/steps/data/garden/energy/2022-12-12/electricity_mix.meta.yml @@ -5,9 +5,9 @@ dataset: short_name: electricity_mix description: | Data is compiled by Our World in Data based on three main sources: - - BP Statistical Review of World Energy. - - Ember Global Electricity Review (2022). - - Ember European Electricity Review (2022). + - [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html). + - [Ember Global Electricity Review (2022)](https://ember-climate.org/data-catalogue/yearly-electricity-data/). + - [Ember European Electricity Review (2022)](https://ember-climate.org/insights/research/european-electricity-review-2022/). Ember compile their global dataset from various sources including: - Eurostat: Annual European generation and import data, and monthly data in some cases where better sources are not available. @@ -18,16 +18,16 @@ dataset: - IRENA: Annual global capacity data for all non-fossil fuel types, and for Other Fossil where available. - WRI: Annual global capacity data for Other Fossil where other sources are not available. - European carbon intensities rely on data from the European Environment Agency (EEA). - - A complete list of data sources for each individual country in Ember's Global Electricity Review can be found here. - - A complete list of data sources for each individual country in Ember's European Electricity Review can be found here. + - A complete list of data sources for each individual country in Ember's Global Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/03/GER22-Methodology.pdf). + - A complete list of data sources for each individual country in Ember's European Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/02/EER-Methodology.pdf). We rely on Ember as the primary source of electricity consumption data. While BP provides primary energy (not just electricity) consumption data and it provides a longer time-series (dating back to 1965) than Ember (which only dates back to 1990), BP does not provide data for all countries or for all sources of electricity (for example, only Ember provides data on electricity from bioenergy). So, where data from Ember is available for a given country and year, we rely on it as the primary source. We then supplement this with data from BP where data from Ember is not available. Our World in Data has converted absolute electricity production by source to the share in the mix by dividing each by total electricity production. - BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with our region definitions). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. + BP's region definitions sometimes differ from Our World in Data's definitions. For example, BP's North America includes only Canada, Mexico and United States, whereas Our World in Data's North America includes countries in Central America (see a map with [our region definitions](https://ourworldindata.org/world-region-map-definitions)). For this reason, we include in the dataset regions like "North America (BP)" to refer to BP's original data using their definition of the region, as well as "North America", which is data aggregated by Our World in Data using our definition. These aggregates are constructed by adding up (when possible) the contributions from the countries in the region. - BP's region definitions, denoted with "(BP)", are: + [BP's region definitions](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/using-the-review/definitions-and-explanatory-notes.html), denoted with "(BP)", are: * "Asia Pacific (BP)": Brunei, Cambodia, China (Mainland), China Hong Kong SAR (Special Administrative Region), China Macau SAR (Special Administrative Region), Indonesia, Japan, Laos, Malaysia, Mongolia, North Korea, Philippines, Singapore, South Asia (Afghanistan, Bangladesh, India, Myanmar, Nepal, Pakistan and Sri Lanka), South Korea, Taiwan, Thailand, Vietnam, Australia, New Zealand, Papua New Guinea and Oceania. * "Australasia (BP)": Australia, New Zealand. * "CIS (BP)" - Commonwealth of Independent States: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russian Federation, Tajikistan, Turkmenistan, Uzbekistan. @@ -53,33 +53,29 @@ dataset: * "North America" - All North American countries + "Other Caribbean (BP)" + "Other North America (BP)". * "Oceania" - All Oceanian countries. * "South America" - All South American countries + "Other South America (BP)". - Where the individual countries in each region are defined in this map. Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions in this map. + Where the individual countries in each region are defined [in this map](https://ourworldindata.org/world-region-map-definitions). Additional BP regions are ignored, since they belong to other regions already included (e.g. the data for "Other Western Africa (BP)" is included in "Other Africa (BP)"). Finally, income groups are constructed following the definitions [in this map](https://ourworldindata.org/grapher/world-banks-income-groups). - Ember's region definitions, denoted with "(Ember)", are: + [Ember's region definitions](https://ember-climate.org/countries-and-regions/), denoted with "(Ember)", are: * "G20 (Ember)" - Group of Twenty: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, United Kingdom, United States and the 27 members of the European Union. * "G7 (Ember)" - Group of Seven: Canada, France, Germany, Italy, Japan, United Kingdom and United States. * "Latin America and Caribbean (Ember)": Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Aruba, British Virgin Islands, Cayman Islands, Falkland Islands, French Guiana, Guadeloupe, Martinique, Montserrat, Puerto Rico, Turks and Caicos Islands and United States Virgin Islands. * "Middle East (Ember)": Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates and Yemen. * "OECD (Ember)" - Organization For Economic Co-operation and Development: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, Australia, Canada, Chile, Colombia, Israel, Japan, Mexico, New Zealand, South Korea, and United States. sources: - - - name: Our World in Data based on BP Statistical Review of World Energy (2022) - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Our World in Data based on Ember's Global Electricity Review (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Our World in Data based on Ember's European Electricity Review (2022) - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Our World in Data based on BP Statistical Review of World Energy (2022) + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Our World in Data based on Ember's Global Electricity Review (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Our World in Data based on Ember's European Electricity Review (2022) + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: electricity_mix: variables: @@ -91,8 +87,8 @@ tables: name: Bioenergy bioenergy_share_of_electricity__pct: title: Bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy co2_intensity__gco2_kwh: @@ -109,8 +105,8 @@ tables: name: Coal coal_share_of_electricity__pct: title: Coal (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal fossil_generation__twh: @@ -121,8 +117,8 @@ tables: name: Fossil fuels fossil_share_of_electricity__pct: title: Fossil fuels (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil fuels gas_generation__twh: @@ -133,8 +129,8 @@ tables: name: Gas gas_share_of_electricity__pct: title: Gas (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro_generation__twh: @@ -145,8 +141,8 @@ tables: name: Hydropower hydro_share_of_electricity__pct: title: Hydro (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydropower low_carbon_generation__twh: @@ -157,14 +153,14 @@ tables: name: Low-carbon electricity low_carbon_share_of_electricity__pct: title: Low-carbon electricity (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Share of electricity from low-carbon sources net_imports_share_of_demand__pct: title: Net electricity imports as a share of demand (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Net electricity imports as a share of demand nuclear_generation__twh: @@ -175,8 +171,8 @@ tables: name: Nuclear nuclear_share_of_electricity__pct: title: Nuclear (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear oil_generation__twh: @@ -187,8 +183,8 @@ tables: name: Oil oil_share_of_electricity__pct: title: Oil (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Oil other_renewables_excluding_bioenergy_generation__twh: @@ -199,8 +195,8 @@ tables: name: Other renewables, excluding bioenergy other_renewables_excluding_bioenergy_share_of_electricity__pct: title: Other renewables excluding bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, excluding bioenergy other_renewables_including_bioenergy_generation__twh: @@ -211,8 +207,8 @@ tables: name: Other renewables, including bioenergy other_renewables_including_bioenergy_share_of_electricity__pct: title: Other renewables including bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, including bioenergy per_capita_bioenergy_generation__kwh: @@ -333,8 +329,8 @@ tables: name: Renewables renewable_share_of_electricity__pct: title: Renewables (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables numDecimalPlaces: 2 @@ -346,8 +342,8 @@ tables: name: Solar solar_share_of_electricity__pct: title: Solar (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar total_demand__twh: @@ -358,8 +354,8 @@ tables: name: Electricity demand total_electricity_share_of_primary_energy__pct: title: Electricity as share of primary energy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Electricity as share of primary energy total_emissions__mtco2: @@ -388,7 +384,7 @@ tables: name: Wind wind_share_of_electricity__pct: title: Wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind diff --git a/etl/steps/data/garden/energy/2022-12-12/owid_energy.meta.yml b/etl/steps/data/garden/energy/2022-12-12/owid_energy.meta.yml index f52e2076000..a84a897820c 100644 --- a/etl/steps/data/garden/energy/2022-12-12/owid_energy.meta.yml +++ b/etl/steps/data/garden/energy/2022-12-12/owid_energy.meta.yml @@ -6,7 +6,7 @@ dataset: description: | OWID Energy dataset. - This dataset will be loaded by the energy-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the energy-data repository](https://github.com/owid/energy-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' metadata and the content of owid_energy_variable_mapping.csv. diff --git a/etl/steps/data/garden/energy/2022-12-12/uk_historical_electricity.meta.yml b/etl/steps/data/garden/energy/2022-12-12/uk_historical_electricity.meta.yml index abf95853857..066f70c48cb 100644 --- a/etl/steps/data/garden/energy/2022-12-12/uk_historical_electricity.meta.yml +++ b/etl/steps/data/garden/energy/2022-12-12/uk_historical_electricity.meta.yml @@ -4,33 +4,28 @@ dataset: title: UK historical electricity (DUKES, 2022) short_name: uk_historical_electricity description: | - All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy. + All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from [the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy](https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes). - All other data is sourced from the BP's Statistical Review of World Energy and Ember Global Electricity Review. Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. + All other data is sourced from the [BP's Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html) and [Ember Global Electricity Review](https://ember-climate.org/insights/research/global-electricity-review-2022/). Where data from BP is available for a given year, we rely on it as the primary source. We then supplement this with data from Ember where data from BP is not available. sources: - - - name: Digest of UK Energy Statistics - published_by: UK's Department for Business, Energy & Industrial Strategy - date_accessed: 2022-09-21 - url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data - - - name: BP Statistical Review of World Energy - published_by: BP Statistical Review of World Energy - date_accessed: 2022-07-08 - url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html - - - name: Ember's Global Electricity Review - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ - - - name: Ember's European Electricity Review - published_by: Ember - publication_year: 2022 - date_accessed: 2022-08-01 - url: https://ember-climate.org/insights/research/european-electricity-review-2022/ - + - name: Digest of UK Energy Statistics + published_by: UK's Department for Business, Energy & Industrial Strategy + date_accessed: 2022-09-21 + url: https://www.gov.uk/government/statistical-data-sets/historical-electricity-data + - name: BP Statistical Review of World Energy + published_by: BP Statistical Review of World Energy + date_accessed: 2022-07-08 + url: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html + - name: Ember's Global Electricity Review + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/data-catalogue/yearly-electricity-data/ + - name: Ember's European Electricity Review + published_by: Ember + publication_year: 2022 + date_accessed: 2022-08-01 + url: https://ember-climate.org/insights/research/european-electricity-review-2022/ tables: uk_historical_electricity: variables: diff --git a/etl/steps/data/garden/energy/2023-07-10/electricity_mix.meta.yml b/etl/steps/data/garden/energy/2023-07-10/electricity_mix.meta.yml index fa04c0e663b..771ef29a370 100644 --- a/etl/steps/data/garden/energy/2023-07-10/electricity_mix.meta.yml +++ b/etl/steps/data/garden/energy/2023-07-10/electricity_mix.meta.yml @@ -2,9 +2,9 @@ dataset: title: Electricity mix (EI & Ember, 2023) description: | Data is compiled by Our World in Data based on three main sources: - - The Energy Institute (EI) Statistical Review of World Energy. - - Ember Yearly Electricity Data. - - Ember European Electricity Review. + - [The Energy Institute (EI) Statistical Review of World Energy](https://www.energyinst.org/statistical-review). + - [Ember Yearly Electricity Data](https://ember-climate.org/data-catalogue/yearly-electricity-data/). + - [Ember European Electricity Review](https://ember-climate.org/insights/research/european-electricity-review-2022/). Ember compile their global dataset from various sources including: - Eurostat: Annual European generation and import data, and monthly data in some cases where better sources are not available. @@ -15,11 +15,10 @@ dataset: - IRENA: Annual global capacity data for all non-fossil fuel types, and for Other Fossil where available. - WRI: Annual global capacity data for Other Fossil where other sources are not available. - European carbon intensities rely on data from the European Environment Agency (EEA). - - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found here. - - A complete list of data sources for each individual country in Ember's European Electricity Review can be found here. + - A complete list of data sources for each individual country in Ember's Yearly Electricity Data can be found [here](https://ember-climate.org/app/uploads/2022/07/Ember-Electricity-Data-Methodology.pdf). + - A complete list of data sources for each individual country in Ember's European Electricity Review can be found [here](https://ember-climate.org/app/uploads/2022/02/EER-Methodology.pdf). We rely on Ember as the primary source of electricity consumption data. While EI provides primary energy (not just electricity) consumption data and it provides a longer time-series (dating back to 1965) than Ember (which only dates back to 1990), EI does not provide data for all countries or for all sources of electricity (for example, only Ember provides data on electricity from bioenergy). So, where data from Ember is available for a given country and year, we rely on it as the primary source. We then supplement this with data from EI where data from Ember is not available. - tables: electricity_mix: variables: @@ -31,8 +30,8 @@ tables: name: Bioenergy bioenergy_share_of_electricity__pct: title: Bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Bioenergy co2_intensity__gco2_kwh: @@ -49,8 +48,8 @@ tables: name: Coal coal_share_of_electricity__pct: title: Coal (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Coal fossil_generation__twh: @@ -61,8 +60,8 @@ tables: name: Fossil fuels fossil_share_of_electricity__pct: title: Fossil fuels (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Fossil fuels gas_generation__twh: @@ -73,8 +72,8 @@ tables: name: Gas gas_share_of_electricity__pct: title: Gas (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Gas hydro_generation__twh: @@ -85,8 +84,8 @@ tables: name: Hydropower hydro_share_of_electricity__pct: title: Hydro (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Hydropower low_carbon_generation__twh: @@ -97,14 +96,14 @@ tables: name: Low-carbon electricity low_carbon_share_of_electricity__pct: title: Low-carbon electricity (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Share of electricity from low-carbon sources net_imports_share_of_demand__pct: title: Net electricity imports as a share of demand (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Net electricity imports as a share of demand nuclear_generation__twh: @@ -115,8 +114,8 @@ tables: name: Nuclear nuclear_share_of_electricity__pct: title: Nuclear (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Nuclear oil_generation__twh: @@ -127,8 +126,8 @@ tables: name: Oil oil_share_of_electricity__pct: title: Oil (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Oil other_renewables_excluding_bioenergy_generation__twh: @@ -139,8 +138,8 @@ tables: name: Other renewables, excluding bioenergy other_renewables_excluding_bioenergy_share_of_electricity__pct: title: Other renewables excluding bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, excluding bioenergy other_renewables_including_bioenergy_generation__twh: @@ -151,8 +150,8 @@ tables: name: Other renewables, including bioenergy other_renewables_including_bioenergy_share_of_electricity__pct: title: Other renewables including bioenergy (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Other renewables, including bioenergy per_capita_bioenergy_generation__kwh: @@ -280,8 +279,8 @@ tables: name: Renewables renewable_share_of_electricity__pct: title: Renewables (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Renewables numDecimalPlaces: 2 @@ -299,14 +298,14 @@ tables: name: Solar and wind solar_share_of_electricity__pct: title: Solar (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar solar_and_wind_share_of_electricity__pct: title: Solar and wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Solar and wind total_demand__twh: @@ -317,8 +316,8 @@ tables: name: Electricity demand total_electricity_share_of_primary_energy__pct: title: Electricity as share of primary energy (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Electricity as share of primary energy total_emissions__mtco2: @@ -347,7 +346,7 @@ tables: name: Wind wind_share_of_electricity__pct: title: Wind (% electricity) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Wind diff --git a/etl/steps/data/garden/energy/2023-07-10/energy_mix.meta.yml b/etl/steps/data/garden/energy/2023-07-10/energy_mix.meta.yml index 9aaa423cf00..0224bb616ed 100644 --- a/etl/steps/data/garden/energy/2023-07-10/energy_mix.meta.yml +++ b/etl/steps/data/garden/energy/2023-07-10/energy_mix.meta.yml @@ -1,7 +1,7 @@ dataset: title: Energy mix (Energy Institute, 2023) description: | - Raw data on energy consumption is sourced from the Energy Institute Statistical Review of World Energy. + Raw data on energy consumption is sourced from [the Energy Institute Statistical Review of World Energy](https://www.energyinst.org/statistical-review). Primary energy in exajoules (EJ) has been converted to TWh by Our World in Data based on a conversion factor of 1,000,000 / 3,600 (~277.778). @@ -9,11 +9,11 @@ dataset: Also, for non-fossil based electricity, there are two ways to define primary energy: * One is "direct primary energy", which corresponds to electricity generation (in TWh). * The other is "input-equivalent primary energy" (also called "primary energy using the substitution method"). - This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in the Statistical Review methodology document. For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. + This is the amount of fuel that would be required by thermal power stations to generate the reported electricity, as explained in [the Statistical Review methodology document](https://www.energyinst.org/__data/assets/pdf_file/0003/1055541/Methodology.pdf). For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in fossil fuel production and provides a better approximation of each source's share of "final energy" consumption. Additional metrics have been calculated by Our World in Data: - Annual change in energy consumption by source: this is calculated as the difference from the previous year. - % of total primary energy: calculated as each source's share of primary energy (direct energy and primary energy using the substitution method) from all sources. - Per capita energy by source: calculated as primary energy consumption by source, divided by population. - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). diff --git a/etl/steps/data/garden/energy/2023-07-10/fossil_fuel_production.meta.yml b/etl/steps/data/garden/energy/2023-07-10/fossil_fuel_production.meta.yml index a0a1cb0c2d8..4ddf41f4508 100644 --- a/etl/steps/data/garden/energy/2023-07-10/fossil_fuel_production.meta.yml +++ b/etl/steps/data/garden/energy/2023-07-10/fossil_fuel_production.meta.yml @@ -1,7 +1,7 @@ dataset: title: Fossil fuel production (EI & Shift, 2023) description: | - This dataset on fossil fuel production is generated by combining the latest data from the Energy Institute Statistical Review of World Energy and The Shift Dataportal. + This dataset on fossil fuel production is generated by combining the latest data from [the Energy Institute Statistical Review of World Energy](https://www.energyinst.org/statistical-review) and [The Shift Dataportal](https://www.theshiftdataportal.org/energy). The Energy Institute provides fossil fuel production data from 1965 onwards (and crude prices from 1861 onwards). The Shift Dataportal provides long-term data from 1900, but only extends to 2016. @@ -9,86 +9,85 @@ dataset: We have converted primary production in exajoules to terawatt-hours using the conversion factor: 1,000,000 / 3,600 ~ 278. - Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. - + Production per capita has been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). tables: fossil_fuel_production: variables: annual_change_in_coal_production__pct: - title: "Annual change in coal production (%)" - short_unit: "%" - unit: "%" + title: Annual change in coal production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_coal_production__twh: - title: "Annual change in coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in coal production" + name: Annual change in coal production annual_change_in_gas_production__pct: - title: "Annual change in gas production (%)" - short_unit: "%" - unit: "%" + title: Annual change in gas production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_gas_production__twh: - title: "Annual change in gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in gas production" + name: Annual change in gas production annual_change_in_oil_production__pct: - title: "Annual change in oil production (%)" - short_unit: "%" - unit: "%" + title: Annual change in oil production (%) + short_unit: '%' + unit: '%' display: - name: "Annual change in oil production" + name: Annual change in oil production annual_change_in_oil_production__twh: - title: "Annual change in oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Annual change in oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Annual change in oil production" + name: Annual change in oil production coal_production__twh: - title: "Coal production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Coal production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Coal production" + name: Coal production numDecimalPlaces: 0 coal_production_per_capita__kwh: - title: "Coal production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Coal production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Coal production per capita" + name: Coal production per capita numDecimalPlaces: 0 gas_production__twh: - title: "Gas production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Gas production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Gas production" + name: Gas production numDecimalPlaces: 0 gas_production_per_capita__kwh: - title: "Gas production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Gas production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Gas production per capita" + name: Gas production per capita numDecimalPlaces: 0 oil_production__twh: - title: "Oil production (TWh)" - short_unit: "TWh" - unit: "terawatt-hours" + title: Oil production (TWh) + short_unit: TWh + unit: terawatt-hours display: - name: "Oil production" + name: Oil production numDecimalPlaces: 0 oil_production_per_capita__kwh: - title: "Oil production per capita (kWh)" - short_unit: "kWh" - unit: "kilowatt-hours" + title: Oil production per capita (kWh) + short_unit: kWh + unit: kilowatt-hours display: - name: "Oil production per capita" + name: Oil production per capita numDecimalPlaces: 0 diff --git a/etl/steps/data/garden/energy/2023-07-10/owid_energy.meta.yml b/etl/steps/data/garden/energy/2023-07-10/owid_energy.meta.yml index 4ec4e2531c0..d41f5cfd76c 100644 --- a/etl/steps/data/garden/energy/2023-07-10/owid_energy.meta.yml +++ b/etl/steps/data/garden/energy/2023-07-10/owid_energy.meta.yml @@ -3,7 +3,7 @@ dataset: description: | OWID Energy dataset. - This dataset will be loaded by the energy-data repository, to create a csv file of the dataset that can be downloaded in one click. + This dataset will be loaded by [the energy-data repository](https://github.com/owid/energy-data), to create a csv file of the dataset that can be downloaded in one click. # Dataset sources will be created in the step by combining all component datasets' sources. # Also, table metadata will be built from the tables' metadata and the content of owid_energy_variable_mapping.csv. diff --git a/etl/steps/data/garden/energy/2023-07-10/photovoltaic_cost_and_capacity.meta.yml b/etl/steps/data/garden/energy/2023-07-10/photovoltaic_cost_and_capacity.meta.yml index 953e91cdde3..4b63e0f1f5b 100644 --- a/etl/steps/data/garden/energy/2023-07-10/photovoltaic_cost_and_capacity.meta.yml +++ b/etl/steps/data/garden/energy/2023-07-10/photovoltaic_cost_and_capacity.meta.yml @@ -7,21 +7,20 @@ dataset: Photovoltaic cost data between 2004 and 2009 has been taken from Farmer & Lafond (2016). - According to Farmer & Lafond (2016), the data are mostly taken from the Santa-Fe Performance Curve DataBase, accessible at pcdb.santafe.edu. The database has been constructed from personal communications and from Colpier and Cornland (2002), Goldemberg et al. (2004), Lieberman (1984), Lipman and Sperling (1999), Zhao (1999), McDonald and Schrattenholzer (2001), Neij et al. (2003), Moore (2006), Nemet (2006), Schilling and Esmundo (2009). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from Koomey and Hultman (2007) and Cooper (2009). The DNA sequencing data is from Wetterstrand (2015) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. + According to Farmer & Lafond (2016), the data are mostly taken from the [Santa-Fe Performance Curve DataBase](https://pcdb.santafe.edu/). The database has been constructed from personal communications and from [Colpier and Cornland (2002)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0095), [Goldemberg et al. (2004)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0130), [Lieberman (1984)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0180), [Lipman and Sperling (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0190), [Zhao (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0310), [McDonald and Schrattenholzer (2001)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0205), [Neij et al. (2003)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0235), [Moore (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0215), [Nemet (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0240), [Schilling and Esmundo (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0265). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from [Koomey and Hultman (2007)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0165) and [Cooper (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0100). The DNA sequencing data is from [Wetterstrand (2015)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0290) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. Prices from Farmer & Lafond (2016) have been converted to 2021 US$ using the US GDP deflator: https://www.multpl.com/gdp-deflator/table/by-year Photovoltaic capacity data between 2004 and 2021 has been taken from IRENA. Photovoltaic cost data between 2010 and 2021 has been taken from IRENA. - tables: photovoltaic_cost_and_capacity: variables: cost: title: Solar photovoltaic module price - short_unit: '$/W' - unit: '2021 US$ per Watt' + short_unit: $/W + unit: 2021 US$ per Watt description: | Global average price of solar photovoltaic modules. @@ -34,8 +33,8 @@ tables: title: Solar photovoltaic cumulative capacity description: | Global cumulative capacity of solar photovoltaics. - short_unit: 'MW' - unit: 'megawatts' + short_unit: MW + unit: megawatts cumulative_capacity_source: title: Data source for cumulative capacity data unit: '' diff --git a/etl/steps/data/garden/energy/2023-07-10/primary_energy_consumption.meta.yml b/etl/steps/data/garden/energy/2023-07-10/primary_energy_consumption.meta.yml index 3634d9b5e35..99ae06e4109 100644 --- a/etl/steps/data/garden/energy/2023-07-10/primary_energy_consumption.meta.yml +++ b/etl/steps/data/garden/energy/2023-07-10/primary_energy_consumption.meta.yml @@ -2,22 +2,21 @@ dataset: title: Primary energy consumption (EI & EIA, 2023) description: | Primary energy consumption data was compiled by Our World in Data based on two key data sources: - 1. Energy Institute (EI) Statistical Review of World Energy. - 2. International energy data from the U.S. Energy Information Administration (EIA). + 1. [Energy Institute (EI) Statistical Review of World Energy](https://www.energyinst.org/statistical-review). + 2. [International energy data from the U.S. Energy Information Administration (EIA)](https://www.eia.gov/international/data/world/total-energy/more-total-energy-data). EI provides the longest and most up-to-date time-series of primary energy. However, it does not provide data for all countries. We have therefore supplemented this dataset with energy data from the EIA. Where EI provides data for a given country, this data is adopted; for countries where this data is missing, we rely on EIA energy figures. - Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on different sources. - - To calculate energy per unit of GDP, we use total real GDP figures from the Maddison Project Database, version 2020. + Per capita figures have been calculated using a population dataset that is built and maintained by Our World in Data, based on [different sources](https://ourworldindata.org/population-sources). + To calculate energy per unit of GDP, we use total real GDP figures from [the Maddison Project Database, version 2020](https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020). tables: primary_energy_consumption: variables: annual_change_in_primary_energy_consumption__pct: title: Annual change in primary energy consumption (%) - short_unit: "%" - unit: "%" + short_unit: '%' + unit: '%' display: name: Annual change in primary energy consumption annual_change_in_primary_energy_consumption__twh: @@ -30,7 +29,9 @@ tables: title: GDP short_unit: $ unit: 2011 int-$ - description: Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over + time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. display: numDecimalPlaces: 0 population: diff --git a/etl/steps/data/garden/energy/2023-07-10/uk_historical_electricity.meta.yml b/etl/steps/data/garden/energy/2023-07-10/uk_historical_electricity.meta.yml index 515249c7019..d5922e00800 100644 --- a/etl/steps/data/garden/energy/2023-07-10/uk_historical_electricity.meta.yml +++ b/etl/steps/data/garden/energy/2023-07-10/uk_historical_electricity.meta.yml @@ -1,10 +1,9 @@ dataset: title: UK historical electricity (DUKES, 2023c) description: | - All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy. - - All other data is sourced from the the Energy Institute (EI) Statistical Review of World Energy and Ember's Yearly Electricity Data. Where data from Ember is available for a given year, we rely on it as the primary source. We then supplement this with data from EI where data from Ember is not available. + All data prior to 1985 (and prior to 1965 in the case of renewables), is sourced from [the Digest of UK Energy Statistics (DUKES), published by the UK's Department for Business, Energy & Industrial Strategy](https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes). + All other data is sourced from the [the Energy Institute (EI) Statistical Review of World Energy](https://www.energyinst.org/statistical-review) and [Ember's Yearly Electricity Data](https://ember-climate.org/data-catalogue/yearly-electricity-data/). Where data from Ember is available for a given year, we rely on it as the primary source. We then supplement this with data from EI where data from Ember is not available. tables: uk_historical_electricity: variables: diff --git a/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.meta.yml b/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.meta.yml index 51176b6b57c..e1eaa51406a 100644 --- a/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.meta.yml +++ b/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.meta.yml @@ -15,53 +15,44 @@ all_sources: description: The ACD2EPR 2021 dataset links ACD (Armed Conflict Database) 20.1 conflicts to Ethnic Power Relations-Core 2021 groups. definitions: - - ethnic_group: - description: &description_ethnic_group | - The Ethnic Power Relations dataset defines ethnicity as any subjectively experienced sense of commonality based on the belief in common ancestry and shared culture. Given this definition, an ethnic group (i.e. a group of individuals sharing a common ethnicity) is included in the EPR Core dataset if it is politically relevant at least once in the sample period. An ethnic group is classified as politically relevant if at least one political organization claims to represent it in national politics or if its members are subjected to state-led political discrimination. - - group_relevance: &description_group_relevance | - An ethnic group is deemed relevant in a given group-year if at least one political organization claims to represent it in national politics or if its members are subjected to state-led political discrimination. - - egip: - description: &description_egip | - An ethnic group in power (EGIP) is a politically relevant ethnic group which has access to power, in one of these options: -
    -
  1. The group rules alone:
  2. The group shares power:
    3. -
- - meg: - description: &description_meg | - An ethnic group is marginalized (MEG) if it is politically relevant but does not have access to power. Marginalization can take one of the following forms: - - - autonomy: - description: &description_autonomy | - For a group to be coded as regionally autonomous, two conditions must be jointly satisfied: - 1. There is a meaningful and active regional executive organ of some type that operates below the state level (for example, the departmental, provincial, or district level) but above the local administrative level. - 2. Group representation is not token: group members exert actual influence on the decisions of this entity and their representatives act in line with the group’s local interests. - - The term “meaningful” here refers to executive organs that carry out core competencies of the state, involving, for example, cultural rights (language and education) and/or significant economic autonomy (for example, the right to levy taxes, or very substantial spending autonomy). - - acd_conflict: - description: &description_acd_conflict | - An ACD (Armed Conflict Database) conflict for this dataset includes: - Each conflict is assigned a unique UCDP (Uppsala Conflict Data Program) ID. ACD conflicts are merged with the Ethnic Power Relations country-level data by assigning each country-year observation one or several UCDP IDs if the ACD dataset reports an ongoing conflict in the respective country and year. - - conflict_onset: - description: &description_conflict_onset | - A conflict onset occurs if a country experiences an intrastate conflict in a given year, and the respective conflict (as identified via its UCDP ID) has been inactive in the given country in the previous two calendar years. - The dataset also offers conflict onset variables that distinguish between ethnic and non-ethnic conflicts. Conflict onsets are coded as ethnic if at least one ethnic group is linked to the respective ACD conflict in the onset year. - - The KO option refers to "Keep Ongoing". Conflict onset variables with the KO option take the value of 1 for country-years in which a country experiences conflict onset, and 0 in all other years. - The DO option refers to "Drop Ongoing". Conflict onset variables with the DO option indicate conflict in the same manner as the KO variables, but are censored if a given country has experienced any conflict in the previous two calendar years. - - conflict_incidence: - description: &description_conflict_incidence | - This variable assumes the value of 1 in years when at least one ACD conflict episode is ongoing, and 0 in all other years. + ethnic_group: |- + The Ethnic Power Relations dataset defines ethnicity as any subjectively experienced sense of commonality based on the belief in common ancestry and shared culture. Given this definition, an ethnic group (i.e. a group of individuals sharing a common ethnicity) is included in the EPR Core dataset if it is politically relevant at least once in the sample period. An ethnic group is classified as politically relevant if at least one political organization claims to represent it in national politics or if its members are subjected to state-led political discrimination. + group_relevance: |- + An ethnic group is deemed relevant in a given group-year if at least one political organization claims to represent it in national politics or if its members are subjected to state-led political discrimination. + egip: |- + An ethnic group in power (EGIP) is a politically relevant ethnic group which has access to power, in one of these options: + 1. The group rules alone: + * Monopoly: Elite members hold power in the executive to the exclusion of members of all other ethnic groups. + * Dominance: Elite members hold dominant power in the executive, but there is some limited inclusion of "token" members of other groups who however do not have real influence on decision making. + + 2. The group shares power: + * Senior Partner: Representatives of the group participate as senior partners in a formal or informal power-sharing arrangement. By power sharing means any arrangement that divides executive power among leaders who claim to represent particular ethnic groups and who have real influence on political decision making. + * Junior Partner: Representatives participate as junior partners in government, reflected in the number and importance of the positions controlled by group members. + meg: |- + An ethnic group is marginalized (MEG) if it is politically relevant but does not have access to power. Marginalization can take one of the following forms: + * Powerless: Elite representatives hold no political power (or do not have influence on decision making) at the national level of executive power - although without being explicitly discriminated against. + * Discrimination: Group members are subjected to active, intentional, and targeted discrimination by the state, with the intent of excluding them from political power. Such active discrimination can be either formal or informal, but always refers to the domain of public politics (excluding discrimination in the socio-economic sphere). + * Self-exclusion: Applies to groups that have excluded themselves from central state power, in the sense that they control a particular territory of the state which they have declared independent from the central government. + autonomy: |- + For a group to be coded as regionally autonomous, two conditions must be jointly satisfied: + 1. There is a meaningful and active regional executive organ of some type that operates below the state level (for example, the departmental, provincial, or district level) but above the local administrative level. + 2. Group representation is not token: group members exert actual influence on the decisions of this entity and their representatives act in line with the group’s local interests. + + The term “meaningful” here refers to executive organs that carry out core competencies of the state, involving, for example, cultural rights (language and education) and/or significant economic autonomy (for example, the right to levy taxes, or very substantial spending autonomy). + acd_conflict: |- + An ACD (Armed Conflict Database) conflict for this dataset includes: + * Intrastate conflict: A conflict between a government and a non-governmental party, with no interference from other countries. + * Intrastate conflict internationalized: An armed conflict between a government and a non-government party where the government side, the opposing side, or both sides, receive troop support from other governments that actively participate in the conflict. + + Each conflict is assigned a unique UCDP (Uppsala Conflict Data Program) ID. ACD conflicts are merged with the Ethnic Power Relations country-level data by assigning each country-year observation one or several UCDP IDs if the ACD dataset reports an ongoing conflict in the respective country and year. + conflict_onset: |- + A conflict onset occurs if a country experiences an intrastate conflict in a given year, and the respective conflict (as identified via its UCDP ID) has been inactive in the given country in the previous two calendar years. + The dataset also offers conflict onset variables that distinguish between ethnic and non-ethnic conflicts. Conflict onsets are coded as ethnic if at least one ethnic group is linked to the respective ACD conflict in the onset year. + + The KO option refers to "Keep Ongoing". Conflict onset variables with the KO option take the value of 1 for country-years in which a country experiences conflict onset, and 0 in all other years. + The DO option refers to "Drop Ongoing". Conflict onset variables with the DO option indicate conflict in the same manner as the KO variables, but are censored if a given country has experienced any conflict in the previous two calendar years. + conflict_incidence: |- + This variable assumes the value of 1 in years when at least one ACD conflict episode is ongoing, and 0 in all other years. dataset: short_name: ethnic_power_relations @@ -75,10 +66,12 @@ tables: variables: egip_groups_count: title: Number of ethnic groups in power (EGIP) - description: - - Count variable indicating the number of EGIP groups in this country.
- - *description_ethnic_group - - *description_egip + description: | + Count variable indicating the number of EGIP groups in this country. + + {definitions.ethnic_group} + + {definitions.egip} unit: "" short_unit: "" display: @@ -88,10 +81,12 @@ tables: - *source-epr excl_groups_count: title: Number of marginalized ethnic groups (MEG) - description: - - Count variable indicating the number of MEG groups in this country.
- - *description_ethnic_group - - *description_meg + description: | + Count variable indicating the number of MEG groups in this country. + + {definitions.ethnic_group} + + {definitions.meg} unit: "" short_unit: "" display: @@ -101,9 +96,10 @@ tables: - *source-epr regaut_groups_count: title: Number of groups with regional autonomy - description: - - Count variable indicating number of groups with regional autonomy in this country.
- - *description_autonomy + description: | + Count variable indicating number of groups with regional autonomy in this country. + + {definitions.autonomy} unit: "" short_unit: "" display: @@ -113,11 +109,14 @@ tables: - *source-epr regaut_excl_groups_count: title: Number of marginalized ethnic groups (MEG) with regional autonomy - description: - - Count variable indicating number of MEG groups with regional autonomy in this country.
- - *description_ethnic_group - - *description_meg - - *description_autonomy + description: | + Count variable indicating number of MEG groups with regional autonomy in this country. + + {definitions.ethnic_group} + + {definitions.meg} + + {definitions.autonomy} unit: "" short_unit: "" display: @@ -127,11 +126,14 @@ tables: - *source-epr regaut_egip_groups_count: title: Number of ethnic groups in power (EGIP) with regional autonomy - description: - - Count variable indicating number of EGIP groups with regional autonomy in this country.
- - *description_ethnic_group - - *description_egip - - *description_autonomy + description: | + Count variable indicating number of EGIP groups with regional autonomy in this country. + + {definitions.ethnic_group} + + {definitions.egip} + + {definitions.autonomy} unit: "" short_unit: "" display: @@ -141,9 +143,10 @@ tables: - *source-epr rlvt_groups_count: title: Number of relevant groups - description: - - Count variable indicating the number of relevant groups in this country.
- - *description_group_relevance + description: | + Count variable indicating the number of relevant groups in this country. + + {definitions.group_relevance} unit: "" short_unit: "" display: @@ -153,9 +156,10 @@ tables: - *source-epr actv_groups_count: title: Number of active groups - description: - - Count variable indicating the number of active groups in this country.
- - A group is considered active if it is phisically present in a country and is not currently represented by an active ancestor or descendant. + description: | + Count variable indicating the number of active groups in this country. + + A group is considered active if it is phisically present in a country and is not currently represented by an active ancestor or descendant. unit: "" short_unit: "" display: @@ -165,10 +169,12 @@ tables: - *source-epr lpop: title: Share of population ethnically relevant - description: - - Sum of the ethnically relevant population in this country (as a fraction of total population).
- - *description_ethnic_group - - *description_group_relevance + description: | + Sum of the ethnically relevant population in this country (as a fraction of total population). + + {definitions.ethnic_group} + + {definitions.group_relevance} unit: "%" short_unit: "%" display: @@ -176,10 +182,12 @@ tables: numDecimalPlaces: 1 egippop: title: Share of population in ethnic groups in power (EGIP) - description: - - Sum of the population of all EGIP groups in this country (as a fraction of total population).
- - *description_ethnic_group - - *description_egip + description: | + Sum of the population of all EGIP groups in this country (as a fraction of total population). + + {definitions.ethnic_group} + + {definitions.egip} unit: "%" short_unit: "%" display: @@ -189,11 +197,14 @@ tables: - *source-epr legippop: title: Share of ethnically relevant population in ethnic groups in power (EGIP) - description: - - EGIP population as a fraction of ethnically relevant population in this country.
- - *description_ethnic_group - - *description_group_relevance - - *description_egip + description: | + EGIP population as a fraction of ethnically relevant population in this country. + + {definitions.ethnic_group} + + {definitions.group_relevance} + + {definitions.egip} unit: "%" short_unit: "%" display: @@ -203,10 +214,12 @@ tables: - *source-epr exclpop: title: Share of population in marginalized ethnic groups (MEG) - description: - - Sum of the population of all MEG groups in this country (as a fraction of total population).
- - *description_ethnic_group - - *description_meg + description: | + Sum of the population of all MEG groups in this country (as a fraction of total population). + + {definitions.ethnic_group} + + {definitions.meg} unit: "%" short_unit: "%" display: @@ -216,11 +229,14 @@ tables: - *source-epr restpop: title: Share of the population not belonging to an ethnically relevant group - description: - - Share of the population that is not part of an ethnic group in power (EGIP) or a marginalized ethnic group (MEG).
- - *description_ethnic_group - - *description_egip - - *description_meg + description: | + Share of the population that is not part of an ethnic group in power (EGIP) or a marginalized ethnic group (MEG). + + {definitions.ethnic_group} + + {definitions.egip} + + {definitions.meg} unit: "%" short_unit: "%" display: @@ -230,11 +246,14 @@ tables: - *source-epr lexclpop: title: Share of ethnically relevant population in marginalized ethnic groups (MEG) - description: - - MEG population as a fraction of ethnically relevant population in this country.
- - *description_ethnic_group - - *description_group_relevance - - *description_meg + description: | + MEG population as a fraction of ethnically relevant population in this country. + + {definitions.ethnic_group} + + {definitions.group_relevance} + + {definitions.meg} unit: "%" short_unit: "%" display: @@ -244,8 +263,8 @@ tables: - *source-epr discrimpop: title: Share of population discriminated - description: - - Sum of discriminated population in this country (as a fraction of total population).
+ description: | + Sum of discriminated population in this country (as a fraction of total population). unit: "%" short_unit: "%" display: @@ -255,10 +274,12 @@ tables: - *source-epr ldiscrimpop: title: Share of ethnically relevant population which is discriminated - description: - - Sum of discriminated population as a fraction of ethnically relevant population in this country.
- - *description_ethnic_group - - *description_group_relevance + description: | + Sum of discriminated population as a fraction of ethnically relevant population in this country. + + {definitions.ethnic_group} + + {definitions.group_relevance} unit: "%" short_unit: "%" display: @@ -268,10 +289,12 @@ tables: - *source-epr maxexclpop: title: Share of population of the largest marginalized ethnic group (MEG) - description: - - Size of the largest MEG group in this country (as a fraction of total population).
- - *description_ethnic_group - - *description_meg + description: | + Size of the largest MEG group in this country (as a fraction of total population). + + {definitions.ethnic_group} + + {definitions.meg} unit: "%" short_unit: "%" display: @@ -281,11 +304,14 @@ tables: - *source-epr lmaxexclpop: title: Share of ethnically relevant population in the largest marginalized ethnic group (MEG) - description: - - Size of the largest MEG group in this country as a fraction of ethnically relevant population.
- - *description_ethnic_group - - *description_group_relevance - - *description_meg + description: | + Size of the largest MEG group in this country as a fraction of ethnically relevant population. + + {definitions.ethnic_group} + + {definitions.group_relevance} + + {definitions.meg} unit: "%" short_unit: "%" display: @@ -295,9 +321,10 @@ tables: - *source-epr regautpop: title: Share of population with regional autonomy - description: - - Sum of population with regional autonomy in this country (as a fraction of total population).
- - *description_autonomy + description: | + Sum of population with regional autonomy in this country (as a fraction of total population). + + {definitions.autonomy} unit: "%" short_unit: "%" display: @@ -307,11 +334,14 @@ tables: - *source-epr regautexclpop: title: Share of population with regional autonomy and in a marginalized ethnic group (MEG) - description: - - Sum of population with regional autonomy and excluded (MEG) in this country (as a fraction of total population).
- - *description_ethnic_group - - *description_meg - - *description_autonomy + description: | + Sum of population with regional autonomy and excluded (MEG) in this country (as a fraction of total population). + + {definitions.ethnic_group} + + {definitions.meg} + + {definitions.autonomy} unit: "%" short_unit: "%" display: @@ -321,11 +351,14 @@ tables: - *source-epr regautegippop: title: Share of population with regional autonomy and in an ethnic group in power (EGIP) - description: - - Sum of population with regional autonomy and included (EGIP) in this country (as a fraction of total population)
- - *description_ethnic_group - - *description_egip - - *description_autonomy + description: | + Sum of population with regional autonomy and included (EGIP) in this country (as a fraction of total population) + + {definitions.ethnic_group} + + {definitions.egip} + + {definitions.autonomy} unit: "%" short_unit: "%" display: @@ -335,10 +368,12 @@ tables: - *source-epr lpop_headcount: title: Population ethnically relevant - description: - - Sum of the ethnically relevant population in this country.
- - *description_ethnic_group - - *description_group_relevance + description: | + Sum of the ethnically relevant population in this country. + + {definitions.ethnic_group} + + {definitions.group_relevance} unit: "" short_unit: "" display: @@ -346,10 +381,12 @@ tables: numDecimalPlaces: 0 egippop_headcount: title: Population in ethnic groups in power (EGIP) - description: - - Population of all EGIP groups in this country.
- - *description_ethnic_group - - *description_egip + description: | + Population of all EGIP groups in this country. + + {definitions.ethnic_group} + + {definitions.egip} unit: "" short_unit: "" display: @@ -359,10 +396,12 @@ tables: - *source-epr exclpop_headcount: title: Population in marginalized ethnic groups (MEG) - description: - - Population of all MEG groups in this country.
- - *description_ethnic_group - - *description_meg + description: | + Population of all MEG groups in this country. + + {definitions.ethnic_group} + + {definitions.meg} unit: "" short_unit: "" display: @@ -372,11 +411,14 @@ tables: - *source-epr restpop_headcount: title: Population not belonging to an ethnically relevant group - description: - - Population that is not part of an ethnic group in power (EGIP) or a marginalized ethnic group (MEG).
- - *description_ethnic_group - - *description_egip - - *description_meg + description: | + Population that is not part of an ethnic group in power (EGIP) or a marginalized ethnic group (MEG). + + {definitions.ethnic_group} + + {definitions.egip} + + {definitions.meg} unit: "" short_unit: "" display: @@ -386,8 +428,8 @@ tables: - *source-epr discrimpop_headcount: title: Population discriminated - description: - - Discriminated population in this country.
+ description: | + Discriminated population in this country. unit: "" short_unit: "" display: @@ -397,10 +439,12 @@ tables: - *source-epr maxexclpop_headcount: title: Population of the largest marginalized ethnic group (MEG) - description: - - Size of the largest MEG group in this country.
- - *description_ethnic_group - - *description_meg + description: | + Size of the largest MEG group in this country. + + {definitions.ethnic_group} + + {definitions.meg} unit: "" short_unit: "" display: @@ -410,9 +454,10 @@ tables: - *source-epr regautpop_headcount: title: Population with regional autonomy - description: - - Sum of population with regional autonomy in this country.
- - *description_autonomy + description: | + Sum of population with regional autonomy in this country. + + {definitions.autonomy} unit: "" short_unit: "" display: @@ -422,11 +467,14 @@ tables: - *source-epr regautexclpop_headcount: title: Population with regional autonomy and in a marginalized ethnic group (MEG) - description: - - Sum of population with regional autonomy and excluded (MEG) in this country.
- - *description_ethnic_group - - *description_meg - - *description_autonomy + description: | + Sum of population with regional autonomy and excluded (MEG) in this country. + + {definitions.ethnic_group} + + {definitions.meg} + + {definitions.autonomy} unit: "" short_unit: "" display: @@ -436,11 +484,14 @@ tables: - *source-epr regautegippop_headcount: title: Population with regional autonomy and in an ethnic group in power (EGIP) - description: - - Sum of population with regional autonomy and included (EGIP) in this country
- - *description_ethnic_group - - *description_egip - - *description_autonomy + description: | + Sum of population with regional autonomy and included (EGIP) in this country + + {definitions.ethnic_group} + + {definitions.egip} + + {definitions.autonomy} unit: "" short_unit: "" display: @@ -450,10 +501,12 @@ tables: - *source-epr cntr_relevance: title: Relevance - description: - - '"R" indicates countries where ethnicity is coded as being relevant at least once in the sample period; "P" indicates countries where only a placeholder group is coded.
' - - *description_ethnic_group - - *description_group_relevance + description: | + '"R" indicates countries where ethnicity is coded as being relevant at least once in the sample period; "P" indicates countries where only a placeholder group is coded.' + + {definitions.ethnic_group} + + {definitions.group_relevance} unit: "" short_unit: "" display: @@ -462,8 +515,7 @@ tables: - *source-epr nstar: title: Index N* of ethnonationalist exclusiveness - description: - - "N*(0.5; 5); see Cederman L.-E. and L. Girardin (2007). Beyond fractionalization: Mapping ethnicity onto nationalist insurgencies. The American Political Science Review 101(1): pp. 173-185." + description: "N*(0.5; 5); see Cederman L.-E. and L. Girardin (2007). Beyond fractionalization: Mapping ethnicity onto nationalist insurgencies. The American Political Science Review 101(1): pp. 173-185." unit: "" short_unit: "" display: @@ -472,11 +524,14 @@ tables: - *source-epr onset_ko_eth_flag: title: Ethnic conflict onset (KO) - description: - - Binary flag indicating ethnic conflict onset / ko option.
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating ethnic conflict onset / ko option. + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -486,11 +541,14 @@ tables: - *source-acd2epr onset_ko_noneth_flag: title: Nonethnic conflict onset (KO) - description: - - Binary flag indicating nonethnic conflict onset / ko option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating nonethnic conflict onset / ko option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -500,11 +558,14 @@ tables: - *source-acd2epr onset_ko_terr_eth_flag: title: Territorial ethnic conflict onset (KO) - description: - - Binary flag indicating territorial ethnic conflict onset / ko option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating territorial ethnic conflict onset / ko option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -514,11 +575,14 @@ tables: - *source-acd2epr onset_ko_gov_eth_flag: title: Governmental ethnic conflict onset (KO) - description: - - Binary flag indicating governmental ethnic conflict onset / ko option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating governmental ethnic conflict onset / ko option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -528,11 +592,14 @@ tables: - *source-acd2epr onset_ko_terr_noneth_flag: title: Territorial nonethnic conflict onset (KO) - description: - - Binary flag indicating territorial nonethnic conflict onset / ko option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating territorial nonethnic conflict onset / ko option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -542,11 +609,14 @@ tables: - *source-acd2epr onset_ko_gov_noneth_flag: title: Governmental nonethnic conflict onset (KO) - description: - - Binary flag indicating governmental nonethnic conflict onset / ko option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating governmental nonethnic conflict onset / ko option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -556,11 +626,14 @@ tables: - *source-acd2epr incidence_eth_flag: title: Ongoing ethnic conflict - description: - - Binary flag indicating ongoing ethnic conflict
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_incidence + description: | + Binary flag indicating ongoing ethnic conflict + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_incidence} unit: "" short_unit: "" display: @@ -570,11 +643,14 @@ tables: - *source-acd2epr incidence_noneth_flag: title: Ongoing non-ethnic conflict - description: - - Binary flag indicating ongoing non-ethnic conflict
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_incidence + description: | + Binary flag indicating ongoing non-ethnic conflict + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_incidence} unit: "" short_unit: "" display: @@ -584,11 +660,14 @@ tables: - *source-acd2epr incidence_terr_eth_flag: title: Ongoing territorial ethnic conflict - description: - - Binary flag indicating ongoing territorial ethnic conflict
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_incidence + description: | + Binary flag indicating ongoing territorial ethnic conflict + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_incidence} unit: "" short_unit: "" display: @@ -598,11 +677,14 @@ tables: - *source-acd2epr incidence_gov_eth_flag: title: Ongoing governmental ethnic conflict - description: - - Binary flag indicating ongoing governmental ethnic conflict
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_incidence + description: | + Binary flag indicating ongoing governmental ethnic conflict + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_incidence} unit: "" short_unit: "" display: @@ -612,11 +694,14 @@ tables: - *source-acd2epr incidence_terr_noneth_flag: title: Ongoing territorial nonethnic conflict - description: - - Binary flag indicating ongoing territorial nonethnic conflict
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_incidence + description: | + Binary flag indicating ongoing territorial nonethnic conflict + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_incidence} unit: "" short_unit: "" display: @@ -626,10 +711,12 @@ tables: - *source-acd2epr incidence_gov_noneth_flag: title: Ongoing governmental nonethnic conflict - description: - - Binary flag indicating ongoing governmental nonethnic conflict
- - *description_acd_conflict - - *description_conflict_incidence + description: | + Binary flag indicating ongoing governmental nonethnic conflict + + {definitions.acd_conflict} + + {definitions.conflict_incidence} unit: "" short_unit: "" display: @@ -639,11 +726,14 @@ tables: - *source-acd2epr onset_do_eth_flag: title: Ethnic conflict onset (DO) - description: - - Binary flag indicating ethnic conflict onset / do option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating ethnic conflict onset / do option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -653,10 +743,12 @@ tables: - *source-acd2epr onset_do_noneth_flag: title: Nonethnic conflict onset (DO) - description: - - Binary flag indicating nonethnic conflict onset / do option
- - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating nonethnic conflict onset / do option + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -666,11 +758,14 @@ tables: - *source-acd2epr onset_do_terr_eth_flag: title: Territorial ethnic conflict onset (DO) - description: - - Binary flag indicating territorial ethnic conflict onset / do option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating territorial ethnic conflict onset / do option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -680,11 +775,14 @@ tables: - *source-acd2epr onset_do_gov_eth_flag: title: Governmental ethnic conflict onset (DO) - description: - - Binary flag indicating governmental ethnic conflict onset / do option
- - *description_ethnic_group - - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating governmental ethnic conflict onset / do option + + {definitions.ethnic_group} + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -694,10 +792,12 @@ tables: - *source-acd2epr onset_do_terr_noneth_flag: title: Territorial nonethnic conflict onset (DO) - description: - - Binary flag indicating territorial nonethnic conflict onset / do option
- - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating territorial nonethnic conflict onset / do option + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: @@ -707,10 +807,12 @@ tables: - *source-acd2epr onset_do_gov_noneth_flag: title: Governmental nonethnic conflict onset (DO) - description: - - Binary flag indicating governmental nonethnic conflict onset / do option
- - *description_acd_conflict - - *description_conflict_onset + description: | + Binary flag indicating governmental nonethnic conflict onset / do option + + {definitions.acd_conflict} + + {definitions.conflict_onset} unit: "" short_unit: "" display: diff --git a/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.py b/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.py index f7193a50e26..00be162d735 100644 --- a/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.py +++ b/etl/steps/data/garden/eth/2023-03-15/ethnic_power_relations.py @@ -276,13 +276,6 @@ def run(dest_dir: str) -> None: # Create a new garden dataset with the same metadata as the meadow dataset. ds_garden = create_dataset(dest_dir, tables=[tb_garden]) - # For now the variable descriptions are stored as a list of strings, this transforms them into a single string - tb_garden = ds_garden["ethnic_power_relations"] - for col in tb_garden.columns: - if isinstance(tb_garden[col].metadata.description, list): - tb_garden[col].metadata.description = "\n".join(tb_garden[col].metadata.description) - ds_garden.add(tb_garden) - # Save changes in the new garden dataset. ds_garden.save() diff --git a/etl/steps/data/garden/gcp/2023-07-10/global_carbon_budget.meta.yml b/etl/steps/data/garden/gcp/2023-07-10/global_carbon_budget.meta.yml index 9c70ad34f54..5a77ee1f6d0 100644 --- a/etl/steps/data/garden/gcp/2023-07-10/global_carbon_budget.meta.yml +++ b/etl/steps/data/garden/gcp/2023-07-10/global_carbon_budget.meta.yml @@ -1,10 +1,10 @@ dataset: title: Global Carbon Budget (Global Carbon Project, 2023b) description: | - The Global Carbon Budget dataset is available here. + The Global Carbon Budget dataset is available [here](https://globalcarbonbudget.org/archive/). Full reference: - Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811-4900, https://doi.org/10.5194/essd-14-4811-2022, 2022. + Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811-4900, https://doi.org/10.5194/essd-14-4811-2022, 2022. Variables include each country, region and World Bank income group's share of the global population; production-based (territorial); and consumption-based (trade-adjusted) carbon dioxide emissions. @@ -12,7 +12,7 @@ dataset: Note that consumption-based emissions are not available for all countries; although those without complete data are a small fraction (3%) of the global total. - Calculation of each country's share of the global population is calculated using our population dataset, based on different sources). + Calculation of each country's share of the global population is calculated using our population dataset, based on [different sources](https://ourworldindata.org/population-sources)). Data on global emissions has been converted by Our World in Data from tonnes of carbon to tonnes of carbon dioxide (CO₂) using a conversion factor of 3.664. @@ -302,7 +302,9 @@ tables: title: "GDP" unit: "2011 international-$" short_unit: "$" - description: "Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries." + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) + and price differences between countries. global_cumulative_emissions_from_cement: title: "Global cumulative CO₂ emissions from cement" unit: "tonnes" diff --git a/etl/steps/data/garden/ggdc/2020-10-01/ggdc_maddison.meta.yml b/etl/steps/data/garden/ggdc/2020-10-01/ggdc_maddison.meta.yml index 6b38960a2c8..25b9ce6ba2f 100644 --- a/etl/steps/data/garden/ggdc/2020-10-01/ggdc_maddison.meta.yml +++ b/etl/steps/data/garden/ggdc/2020-10-01/ggdc_maddison.meta.yml @@ -10,7 +10,8 @@ tables: title: GDP short_unit: $ unit: international-$ in 2011 prices - description: Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. + description: >- + Gross domestic product measured in international-$ using 2011 prices to adjust for price changes over time (inflation) and price differences between countries. Calculated by multiplying GDP per capita with population. display: entityAnnotationsMap: "Western Offshoots (MPD): United States, Canada, Australia and New Zealand" numDecimalPlaces: 0 diff --git a/etl/steps/data/garden/growth/2022-12-19/gdp_historical.meta.yml b/etl/steps/data/garden/growth/2022-12-19/gdp_historical.meta.yml index 6cb2501dd80..cc8e4ba190f 100644 --- a/etl/steps/data/garden/growth/2022-12-19/gdp_historical.meta.yml +++ b/etl/steps/data/garden/growth/2022-12-19/gdp_historical.meta.yml @@ -28,11 +28,9 @@ dataset: short_name: gdp_historical description: | This dataset combines the Maddison Project Database, Maddison Database and World Bank's World Development Indicators current estimations to present the most up-to-date evolution of GDP and GDP per capita in the last millennia. As the global aggregation from the World Bank only starts from 1990, the global GDP data is separated into three parts: - + * From 1990 onward it is exactly the same value estimated by the World Bank (international-$ in 2017 prices). + * Between 1820 and 1990 the World Bank data from 1990 is retroactively adjusted using the global aggregations by Maddison Project Database. + * Between 1 and 1820 the 1820 estimation is retroactively adjusted using growth coming from the Maddison Database 2010 sources: - *source_maddison_project - *source_maddison_database diff --git a/etl/steps/data/garden/lgbt_rights/2023-04-13/equaldex.meta.yml b/etl/steps/data/garden/lgbt_rights/2023-04-13/equaldex.meta.yml index 0edb1b3cc4b..8d57981118e 100644 --- a/etl/steps/data/garden/lgbt_rights/2023-04-13/equaldex.meta.yml +++ b/etl/steps/data/garden/lgbt_rights/2023-04-13/equaldex.meta.yml @@ -26,12 +26,12 @@ tables: Describes the legislation status of homosexual activity, consensual sexual activity between individuals of the same sex. These statuses are possible: -
  1. Legal
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Male illegal, female legal or uncertain
    5. -
  5. Illegal, prison or other penalty
    6. -
  6. Illegal (death penalty as punishment)
+ 1. Legal + 2. Varies by region + 3. Ambiguous + 4. Male illegal, female legal or uncertain + 5. Illegal, prison or other penalty + 6. Illegal (death penalty as punishment) sources: - *source-equaldex display: @@ -44,11 +44,11 @@ tables: Describes the legislation status of the right to change legal gender. This is the legal recognition of sex reassignment by permitting a change of legal gender on an individual's birth certificate. These statuses are possible: -
  1. Legal, surgery not required
    2. -
  2. Legal, but requires surgery
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. Illegal
+ 1. Legal, surgery not required + 2. Legal, but requires surgery + 3. Varies by region + 4. Ambiguous + 5. Illegal sources: - *source-equaldex display: @@ -61,15 +61,15 @@ tables: Describes the legislation status of same-sex marriage. This is marriage and marriage recognition between two people of the same biological sex and/or gender identity. These statuses are possible: -
  1. Legal
    2. -
  2. Civil union or other partnership
    3. -
  3. Foreign same-sex marriages recognized only
    4. -
  4. Unregistered cohabitation
    5. -
  5. Varies by region
    6. -
  6. Ambiguous
    7. -
  7. Unrecognized
    8. -
  8. Unrecognized, same-sex marriage and civil unions banned
    9. -
  9. Not legal
+ 1. Legal + 2. Civil union or other partnership + 3. Foreign same-sex marriages recognized only + 4. Unregistered cohabitation + 5. Varies by region + 6. Ambiguous + 7. Unrecognized + 8. Unrecognized, same-sex marriage and civil unions banned + 9. Not legal sources: - *source-equaldex display: @@ -82,12 +82,12 @@ tables: Describes the legislation status of same-sex adoption. This is the ability for same-sex couples to legally adopt a child. These statuses are possible: -
  1. Legal
    2. -
  2. Married couples only
    3. -
  3. Step-child adoption only
    4. -
  4. Single only
    5. -
  5. Ambiguous
    6. -
  6. Illegal
+ 1. Legal + 2. Married couples only + 3. Step-child adoption only + 4. Single only + 5. Ambiguous + 6. Illegal sources: - *source-equaldex display: @@ -100,10 +100,10 @@ tables: Describes the difference between legal age of consent for homosexual sex and heterosexual sex. These statuses are possible: -
  1. Equal
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Unequal
+ 1. Equal + 2. Varies by region + 3. Ambiguous + 4. Unequal sources: - *source-equaldex display: @@ -116,14 +116,14 @@ tables: Describes the ability for MSMs (men who have sex with men) to donate blood or tissue for organ transplants. A deferral period refers to a waiting time before a man can donate after having sex. These statuses are possible: -
  1. Legal
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Banned (3-month deferral)
    5. -
  5. Banned (6-month deferral)
    6. -
  6. Banned (1-year deferral)
    7. -
  7. Banned (5-year deferral)
    8. -
  8. Banned (indefinite deferral)
+ 1. Legal + 2. Varies by region + 3. Ambiguous + 4. Banned (3-month deferral) + 5. Banned (6-month deferral) + 6. Banned (1-year deferral) + 7. Banned (5-year deferral) + 8. Banned (indefinite deferral) sources: - *source-equaldex display: @@ -136,13 +136,13 @@ tables: Describes censorship or prohibition of discussing, promoting, or teaching LGBTQ+ topics in media, schools, and in the general public. These statuses are possible: -
  1. No censorship
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Other punishment
    5. -
  5. Fine as punishment
    6. -
  6. State-enforced
    7. -
  7. Imprisonment as punishment
+ 1. No censorship + 2. Varies by region + 3. Ambiguous + 4. Other punishment + 5. Fine as punishment + 6. State-enforced + 7. Imprisonment as punishment sources: - *source-equaldex display: @@ -155,10 +155,10 @@ tables: Describes the legal status of conducting sexual orientation changing therapy. These statuses are possible: -
  1. Banned
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Not banned
+ 1. Banned + 2. Varies by region + 3. Ambiguous + 4. Not banned sources: - *source-equaldex display: @@ -171,10 +171,10 @@ tables: Describes the prohibition of discrimination based on sexual orientation and/or gender identity. These statuses are possible: -
  1. Illegal
    2. -
  2. Illegal in some contexts
    3. -
  3. Varies by region
    4. -
  4. No protections
+ 1. Illegal + 2. Illegal in some contexts + 3. Varies by region + 4. No protections sources: - *source-equaldex display: @@ -187,11 +187,11 @@ tables: Describes the prohibition of discrimination based on sexual orientation and/or gender identity in employment, including hiring, promotion, termination, harassment, etc. These statuses are possible: -
  1. Sexual orientation and gender identity
    2. -
  2. Sexual orientation only
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. No protections
+ 1. Sexual orientation and gender identity + 2. Sexual orientation only + 3. Varies by region + 4. Ambiguous + 5. No protections sources: - *source-equaldex display: @@ -204,11 +204,11 @@ tables: Describes the prohibition of discrimination based on sexual orientation and/or gender identity when applying for housing or discrimination by landlords / property owners. These statuses are possible: -
  1. Sexual orientation and gender identity
    2. -
  2. Sexual orientation only
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. No protections
+ 1. Sexual orientation and gender identity + 2. Sexual orientation only + 3. Varies by region + 4. Ambiguous + 5. No protections sources: - *source-equaldex display: @@ -221,11 +221,11 @@ tables: Describes the ability for homosexuals to serve in the military and be open about their sexuality. These statuses are possible: -
  1. Legal
    2. -
  2. "Don't Ask, Don't Tell"
    3. -
  3. Lesbians, gays, bisexuals permitted, transgender people banned
    4. -
  4. Ambiguous
    5. -
  5. Illegal
+ 1. Legal + 2. "Don't Ask, Don't Tell" + 3. Lesbians, gays, bisexuals permitted, transgender people banned + 4. Ambiguous + 5. Illegal sources: - *source-equaldex display: @@ -238,11 +238,11 @@ tables: Describes the legal recognition of non-binary, genderqueer, or third gender identities. These statuses are possible: -
  1. Recognized
    2. -
  2. Intersex only
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. Not legally recognized
+ 1. Recognized + 2. Intersex only + 3. Varies by region + 4. Ambiguous + 5. Not legally recognized sources: - *source-equaldex display: @@ -255,12 +255,12 @@ tables: Describes the legislation status of homosexual activity, consensual sexual activity between individuals of the same sex. These statuses are possible: -
  1. Legal
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Male illegal, female legal or uncertain
    5. -
  5. Illegal, prison or other penalty
    6. -
  6. Illegal (death penalty as punishment)
+ 1. Legal + 2. Varies by region + 3. Ambiguous + 4. Male illegal, female legal or uncertain + 5. Illegal, prison or other penalty + 6. Illegal (death penalty as punishment) sources: - *source-equaldex display: @@ -273,11 +273,11 @@ tables: Describes the legislation status of the right to change legal gender. This is the legal recognition of sex reassignment by permitting a change of legal gender on an individual's birth certificate. These statuses are possible: -
  1. Legal, surgery not required
    2. -
  2. Legal, but requires surgery
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. Illegal
+ 1. Legal, surgery not required + 2. Legal, but requires surgery + 3. Varies by region + 4. Ambiguous + 5. Illegal sources: - *source-equaldex display: @@ -290,15 +290,15 @@ tables: Describes the legislation status of same-sex marriage. This is marriage and marriage recognition between two people of the same biological sex and/or gender identity. These statuses are possible: -
  1. Legal
    2. -
  2. Civil union or other partnership
    3. -
  3. Foreign same-sex marriages recognized only
    4. -
  4. Unregistered cohabitation
    5. -
  5. Varies by region
    6. -
  6. Ambiguous
    7. -
  7. Unrecognized
    8. -
  8. Unrecognized, same-sex marriage and civil unions banned
    9. -
  9. Not legal
+ 1. Legal + 2. Civil union or other partnership + 3. Foreign same-sex marriages recognized only + 4. Unregistered cohabitation + 5. Varies by region + 6. Ambiguous + 7. Unrecognized + 8. Unrecognized, same-sex marriage and civil unions banned + 9. Not legal sources: - *source-equaldex display: @@ -311,12 +311,12 @@ tables: Describes the legislation status of same-sex adoption. This is the ability for same-sex couples to legally adopt a child. These statuses are possible: -
  1. Legal
    2. -
  2. Married couples only
    3. -
  3. Step-child adoption only
    4. -
  4. Single only
    5. -
  5. Ambiguous
    6. -
  6. Illegal
+ 1. Legal + 2. Married couples only + 3. Step-child adoption only + 4. Single only + 5. Ambiguous + 6. Illegal sources: - *source-equaldex display: @@ -329,10 +329,10 @@ tables: Describes the difference between legal age of consent for homosexual sex and heterosexual sex. These statuses are possible: -
  1. Equal
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Unequal
+ 1. Equal + 2. Varies by region + 3. Ambiguous + 4. Unequal sources: - *source-equaldex display: @@ -345,14 +345,14 @@ tables: Describes the ability for MSMs (men who have sex with men) to donate blood or tissue for organ transplants. A deferral period refers to a waiting time before a man can donate after having sex. These statuses are possible: -
  1. Legal
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Banned (3-month deferral)
    5. -
  5. Banned (6-month deferral)
    6. -
  6. Banned (1-year deferral)
    7. -
  7. Banned (5-year deferral)
    8. -
  8. Banned (indefinite deferral)
+ 1. Legal + 2. Varies by region + 3. Ambiguous + 4. Banned (3-month deferral) + 5. Banned (6-month deferral) + 6. Banned (1-year deferral) + 7. Banned (5-year deferral) + 8. Banned (indefinite deferral) sources: - *source-equaldex display: @@ -365,13 +365,13 @@ tables: Describes censorship or prohibition of discussing, promoting, or teaching LGBTQ+ topics in media, schools, and in the general public. These statuses are possible: -
  1. No censorship
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Other punishment
    5. -
  5. Fine as punishment
    6. -
  6. State-enforced
    7. -
  7. Imprisonment as punishment
+ 1. No censorship + 2. Varies by region + 3. Ambiguous + 4. Other punishment + 5. Fine as punishment + 6. State-enforced + 7. Imprisonment as punishment sources: - *source-equaldex display: @@ -384,10 +384,10 @@ tables: Describes the legal status of conducting sexual orientation changing therapy. These statuses are possible: -
  1. Banned
    2. -
  2. Varies by region
    3. -
  3. Ambiguous
    4. -
  4. Not banned
+ 1. Banned + 2. Varies by region + 3. Ambiguous + 4. Not banned sources: - *source-equaldex display: @@ -400,10 +400,10 @@ tables: Describes the prohibition of discrimination based on sexual orientation and/or gender identity. These statuses are possible: -
  1. Illegal
    2. -
  2. Illegal in some contexts
    3. -
  3. Varies by region
    4. -
  4. No protections
+ 1. Illegal + 2. Illegal in some contexts + 3. Varies by region + 4. No protections sources: - *source-equaldex display: @@ -416,11 +416,11 @@ tables: Describes the prohibition of discrimination based on sexual orientation and/or gender identity in employment, including hiring, promotion, termination, harassment, etc. These statuses are possible: -
  1. Sexual orientation and gender identity
    2. -
  2. Sexual orientation only
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. No protections
+ 1. Sexual orientation and gender identity + 2. Sexual orientation only + 3. Varies by region + 4. Ambiguous + 5. No protections sources: - *source-equaldex display: @@ -433,11 +433,11 @@ tables: Describes the prohibition of discrimination based on sexual orientation and/or gender identity when applying for housing or discrimination by landlords / property owners. These statuses are possible: -
  1. Sexual orientation and gender identity
    2. -
  2. Sexual orientation only
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. No protections
+ 1. Sexual orientation and gender identity + 2. Sexual orientation only + 3. Varies by region + 4. Ambiguous + 5. No protections sources: - *source-equaldex display: @@ -450,11 +450,11 @@ tables: Describes the ability for homosexuals to serve in the military and be open about their sexuality. These statuses are possible: -
  1. Legal
    2. -
  2. "Don't Ask, Don't Tell"
    3. -
  3. Lesbians, gays, bisexuals permitted, transgender people banned
    4. -
  4. Ambiguous
    5. -
  5. Illegal
+ 1. Legal + 2. "Don't Ask, Don't Tell" + 3. Lesbians, gays, bisexuals permitted, transgender people banned + 4. Ambiguous + 5. Illegal sources: - *source-equaldex display: @@ -467,11 +467,11 @@ tables: Describes the legal recognition of non-binary, genderqueer, or third gender identities. These statuses are possible: -
  1. Recognized
    2. -
  2. Intersex only
    3. -
  3. Varies by region
    4. -
  4. Ambiguous
    5. -
  5. Not legally recognized
+ 1. Recognized + 2. Intersex only + 3. Varies by region + 4. Ambiguous + 5. Not legally recognized sources: - *source-equaldex display: diff --git a/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.meta.yml b/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.meta.yml index dcab3bdc310..037eab3767b 100644 --- a/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.meta.yml +++ b/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.meta.yml @@ -1,5 +1,5 @@ descriptions: - policy_robustness: &policy_robustness_description | + policy_robustness: |- This policy is not measured in a binary (adopted/not-adopted) scheme; the author follows Frank and colleagues (2010, 2017) in considering that similar policies can meaningfully vary in scope, benefits, punishment, etc. So, he determines the robustness of each policy by reviewing five indicators (between parentheses are the scoring schemes): 1. Proportion of Population Living Under Law: To acknowledge subnational variations (0-1) @@ -9,7 +9,7 @@ descriptions: 5. Evidence of Enforcement: Has been least one case the previous year where this was implemented? (0: no evidence, 1: evidence) At least three different indicators are used to estimate the policy score, with the result that each policy score ranges from 0 to 1. Therefore, a score of 1 corresponds to that policy's most robust scope and implementation. This also means that changes in any indicator will influence each policy’s overall score. - lgbt_index: &lgbt_index_description | + lgbt_index: |- The LGBT+ Policy Index measures a country’s LGBT+ policy landscape by capturing the implementation of 18 different LGBT+ policies. Policies included in the index are limited to those adopted across at least three countries or are explicitly advocated for by transnational activists. These policies are subdivided between: @@ -49,13 +49,13 @@ descriptions: To create the index, the scores for each policy are summed together annually, with progressive policies receiving a positive score and regressive policies receiving a negative. This results in an index ranging from -5 to +13. No country reaches these extremes, demonstrating that countries can get better and worse in their policy environments. The LGBT+ policy index represents a robust and nuanced measure of LGBT+ policy adoption and implementation and is a novel contribution to the literature. By incorporating progressive and regressive LGBT+ policies and variation in implementation beyond a binary coding scheme, this measure captures even fine-grained changes to the LGBT+ policy landscape. - count_yes: &count_yes_description | + count_yes: |- This is the number of countries per region with full implementation of the policy. - count_no: &count_no_description | + count_no: |- This is the number of countries per region with partial or no implementation of the policy. - pop_yes: &pop_yes_description | + pop_yes: |- This is the population per region with full implementation of the policy. - pop_no: &pop_no_description | + pop_no: |- This is the population per region with partial or no implementation of the policy. dataset: title: LGBT+ policies (Velasco, 2020) @@ -104,9 +104,10 @@ tables: variables: equal_age: title: Equal age of consent - description: - - Measures the presence of a law defining the same age of consent between same-sex and different-sex partners.
- - *policy_robustness_description + description: | + Measures the presence of a law defining the same age of consent between same-sex and different-sex partners. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -114,9 +115,10 @@ tables: numDecimalPlaces: 2 unequal_age: title: Unequal age of consent - description: - - Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults.
- - *policy_robustness_description + description: | + Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults. + + {descriptions.policy_robustness} short_unit: "" unit: '' display: @@ -135,9 +137,10 @@ tables: numDecimalPlaces: 0 conversion_therapies: title: Ban on conversion therapies - description: - - Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery.
- - *policy_robustness_description + description: | + Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -145,9 +148,10 @@ tables: numDecimalPlaces: 2 death_penalty: title: Death penalty for same-sex sexual acts - description: - - Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death.
- - *policy_robustness_description + description: | + Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -155,9 +159,10 @@ tables: numDecimalPlaces: 2 employment_discrim: title: Employment discrimination bans - description: - - Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity.
- - *policy_robustness_description + description: | + Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -165,9 +170,10 @@ tables: numDecimalPlaces: 2 gender_surgery: title: Ban on gender assignment surgeries on children - description: - - Measures if bans on gender assignment surgeries on children are adopted.
- - *policy_robustness_description + description: | + Measures if bans on gender assignment surgeries on children are adopted. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -175,9 +181,10 @@ tables: numDecimalPlaces: 0 hate_crimes: title: Hate crime protections - description: - - Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance.
- - *policy_robustness_description + description: | + Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -185,9 +192,10 @@ tables: numDecimalPlaces: 2 incite_hate: title: Incitement to hatred - description: - - Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal
- - *policy_robustness_description + description: | + Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -195,9 +203,10 @@ tables: numDecimalPlaces: 2 joint_adoption: title: Joint adoptions - description: - - Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such.
- - *policy_robustness_description + description: | + Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -205,9 +214,10 @@ tables: numDecimalPlaces: 2 lgb_military: title: LGB military - description: - - Measures if lesbian, gay, and bisexual people are allowed to serve in the military.
- - *policy_robustness_description + description: | + Measures if lesbian, gay, and bisexual people are allowed to serve in the military. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -215,10 +225,12 @@ tables: numDecimalPlaces: 0 lgb_military_ban: title: LGB military ban - description: - - Measures if lesbian, gay, and bisexual people are banned from the military.
- - Variable not among the 18 policies of the index.
- - *policy_robustness_description + description: | + Measures if lesbian, gay, and bisexual people are banned from the military. + + Variable not among the 18 policies of the index. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -226,9 +238,10 @@ tables: numDecimalPlaces: 0 marriage_equality: title: Marriage equality - description: - - Measures if there is no legal distinction between same-sex and different-sex marriages.
- - *policy_robustness_description + description: | + Measures if there is no legal distinction between same-sex and different-sex marriages. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -236,9 +249,10 @@ tables: numDecimalPlaces: 2 marriage_ban: title: Ban on marriage equality - description: - - Measures if same-sex marriages are banned.
- - *policy_robustness_description + description: | + Measures if same-sex marriages are banned. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -246,9 +260,10 @@ tables: numDecimalPlaces: 2 samesex_legal: title: Same-sex sexual acts legal - description: - - Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults.
- - *policy_robustness_description + description: | + Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -256,10 +271,12 @@ tables: numDecimalPlaces: 2 third_gender: title: Third gender recognition - description: - - Measures if a third gender is recognized in the legislation.
- - Variable not among the 18 policies of the index.
- - *policy_robustness_description + description: | + Measures if a third gender is recognized in the legislation. + + Variable not among the 18 policies of the index. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -267,9 +284,10 @@ tables: numDecimalPlaces: 0 trans_military: title: Trasgender military - description: - - Measures if transgender people are allowed to serve in the military.
- - *policy_robustness_description + description: | + Measures if transgender people are allowed to serve in the military. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -277,9 +295,10 @@ tables: numDecimalPlaces: 0 samesex_illegal: title: Same-sex sexual acts illegal - description: - - Measures the presence of a law declaring that same-sex actions are criminalized between consenting adults.
- - *policy_robustness_description + description: | + Measures the presence of a law declaring that same-sex actions are criminalized between consenting adults. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -287,9 +306,10 @@ tables: numDecimalPlaces: 2 civil_unions: title: Civil unions - description: - - Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included.
- - *policy_robustness_description + description: | + Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -297,9 +317,10 @@ tables: numDecimalPlaces: 2 gendermarker: title: Gender marker change - description: - - Measures if the gender marker can be legally changed.
- - *policy_robustness_description + description: | + Measures if the gender marker can be legally changed. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -307,9 +328,10 @@ tables: numDecimalPlaces: 2 propaganda: title: Anti-propaganda laws - description: - - Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”.
- - *policy_robustness_description + description: | + Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”. + + {descriptions.policy_robustness} short_unit: '' unit: '' display: @@ -317,7 +339,8 @@ tables: numDecimalPlaces: 2 policy_index: title: LGBT+ Policy Index - description: *lgbt_index_description + description: | + {descriptions.lgbt_index} short_unit: '' unit: '' display: @@ -325,9 +348,10 @@ tables: numDecimalPlaces: 2 equal_age_yes: title: Equal age of consent ("yes", number of countries) - description: - - Measures the presence of a law defining the same age of consent between same-sex and different-sex partners.
- - *count_yes_description + description: | + Measures the presence of a law defining the same age of consent between same-sex and different-sex partners. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -335,9 +359,10 @@ tables: numDecimalPlaces: 0 unequal_age_yes: title: Unequal age of consent ("yes"/"partially", number of countries) - description: - - Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults.
- - *count_yes_description + description: | + Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults. + + {descriptions.count_yes} short_unit: "" unit: '' display: @@ -345,9 +370,10 @@ tables: numDecimalPlaces: 0 constitution_yes: title: Constitutional protections against discrimination ("yes", number of countries) - description: - - National constitutions are classified as protective against discrimination based on sexual orientation or gender identity if there is explicit language or if judicial cases have set legal precedent for such protections. - - *count_yes_description + description: | + National constitutions are classified as protective against discrimination based on sexual orientation or gender identity if there is explicit language or if judicial cases have set legal precedent for such protections. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -355,9 +381,10 @@ tables: numDecimalPlaces: 0 conversion_therapies_yes: title: Ban on conversion therapies ("yes", number of countries) - description: - - Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery.
- - *count_yes_description + description: | + Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -365,9 +392,10 @@ tables: numDecimalPlaces: 0 death_penalty_yes: title: Death penalty for same-sex sexual acts ("yes"/"partially", number of countries) - description: - - Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death.
- - *count_yes_description + description: | + Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -375,9 +403,10 @@ tables: numDecimalPlaces: 0 employment_discrim_yes: title: Employment discrimination bans ("yes", number of countries) - description: - - Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity.
- - *count_yes_description + description: | + Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -385,9 +414,10 @@ tables: numDecimalPlaces: 0 gender_surgery_yes: title: Ban on gender assignment surgeries on children ("yes", number of countries) - description: - - Measures if bans on gender assignment surgeries on children are adopted.
- - *count_yes_description + description: | + Measures if bans on gender assignment surgeries on children are adopted. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -395,9 +425,10 @@ tables: numDecimalPlaces: 0 hate_crimes_yes: title: Hate crime protections ("yes", number of countries) - description: - - Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance.
- - *count_yes_description + description: | + Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -405,9 +436,10 @@ tables: numDecimalPlaces: 0 incite_hate_yes: title: Incitement to hatred protections ("yes", number of countries) - description: - - Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal
- - *count_yes_description + description: | + Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -415,9 +447,10 @@ tables: numDecimalPlaces: 0 joint_adoption_yes: title: Joint adoptions ("yes", number of countries) - description: - - Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such.
- - *count_yes_description + description: | + Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -425,9 +458,10 @@ tables: numDecimalPlaces: 0 lgb_military_yes: title: LGB military ("yes", number of countries) - description: - - Measures if lesbian, gay, and bisexual people are allowed to serve in the military.
- - *count_yes_description + description: | + Measures if lesbian, gay, and bisexual people are allowed to serve in the military. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -435,9 +469,10 @@ tables: numDecimalPlaces: 0 lgb_military_ban_yes: title: LGB military ban ("yes", number of countries) - description: - - Measures if lesbian, gay, and bisexual people are banned from the military.
- - *count_yes_description + description: | + Measures if lesbian, gay, and bisexual people are banned from the military. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -445,9 +480,10 @@ tables: numDecimalPlaces: 0 marriage_equality_yes: title: Marriage equality ("yes", number of countries) - description: - - Measures if there is no legal distinction between same-sex and different-sex marriages.
- - *count_yes_description + description: | + Measures if there is no legal distinction between same-sex and different-sex marriages. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -455,9 +491,10 @@ tables: numDecimalPlaces: 0 marriage_ban_yes: title: Ban on marriage equality ("yes", number of countries) - description: - - Measures if same-sex marriages are banned.
- - *count_yes_description + description: | + Measures if same-sex marriages are banned. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -465,9 +502,10 @@ tables: numDecimalPlaces: 0 samesex_legal_yes: title: Same-sex sexual acts legal ("yes", number of countries) - description: - - Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults.
- - *count_yes_description + description: | + Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -475,9 +513,10 @@ tables: numDecimalPlaces: 0 third_gender_yes: title: Third gender recognition ("yes", number of countries) - description: - - Measures if a third gender is recognized in the legislation.
- - *count_yes_description + description: | + Measures if a third gender is recognized in the legislation. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -485,9 +524,10 @@ tables: numDecimalPlaces: 0 trans_military_yes: title: Trasgender military ("yes", number of countries) - description: - - Measures if transgender people are allowed to serve in the military.
- - *count_yes_description + description: | + Measures if transgender people are allowed to serve in the military. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -495,9 +535,10 @@ tables: numDecimalPlaces: 0 civil_unions_yes: title: Civil unions ("yes", number of countries) - description: - - Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included.
- - *count_yes_description + description: | + Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -505,9 +546,10 @@ tables: numDecimalPlaces: 0 gendermarker_yes: title: Gender marker change ("yes", number of countries) - description: - - Measures if the gender marker can be legally changed.
- - *count_yes_description + description: | + Measures if the gender marker can be legally changed. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -515,9 +557,10 @@ tables: numDecimalPlaces: 0 propaganda_yes: title: Anti-propaganda laws ("yes"/"partially", number of countries) - description: - - Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”.
- - *count_yes_description + description: | + Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”. + + {descriptions.count_yes} short_unit: '' unit: '' display: @@ -525,9 +568,10 @@ tables: numDecimalPlaces: 0 equal_age_no: title: Equal age of consent ("no"/"partially", number of countries) - description: - - Measures the presence of a law defining the same age of consent between same-sex and different-sex partners.
- - *count_no_description + description: | + Measures the presence of a law defining the same age of consent between same-sex and different-sex partners. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -535,9 +579,10 @@ tables: numDecimalPlaces: 0 unequal_age_no: title: Unequal age of consent ("no", number of countries) - description: - - Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults.
- - *count_no_description + description: | + Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults. + + {descriptions.count_no} short_unit: "" unit: '' display: @@ -545,9 +590,10 @@ tables: numDecimalPlaces: 0 constitution_no: title: Constitutional protections against discrimination ("no"/"partially", number of countries) - description: - - National constitutions are classified as protective against discrimination based on sexual orientation or gender identity if there is explicit language or if judicial cases have set legal precedent for such protections. - - *count_no_description + description: | + National constitutions are classified as protective against discrimination based on sexual orientation or gender identity if there is explicit language or if judicial cases have set legal precedent for such protections. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -555,9 +601,10 @@ tables: numDecimalPlaces: 0 conversion_therapies_no: title: Ban on conversion therapies ("no"/"partially", number of countries) - description: - - Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery.
- - *count_no_description + description: | + Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -565,9 +612,10 @@ tables: numDecimalPlaces: 0 death_penalty_no: title: Death penalty for same-sex sexual acts ("no", number of countries) - description: - - Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death.
- - *count_no_description + description: | + Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -575,9 +623,10 @@ tables: numDecimalPlaces: 0 employment_discrim_no: title: Employment discrimination bans ("no"/"partially", number of countries) - description: - - Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity.
- - *count_no_description + description: | + Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -585,9 +634,10 @@ tables: numDecimalPlaces: 0 gender_surgery_no: title: Ban on gender assignment surgeries on children ("no"/"partially", number of countries) - description: - - Measures if bans on gender assignment surgeries on children are adopted.
- - *count_no_description + description: | + Measures if bans on gender assignment surgeries on children are adopted. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -595,9 +645,10 @@ tables: numDecimalPlaces: 0 hate_crimes_no: title: Hate crime protections ("no"/"partially", number of countries) - description: - - Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance.
- - *count_no_description + description: | + Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -605,9 +656,10 @@ tables: numDecimalPlaces: 0 incite_hate_no: title: Incitement to hatred ("no"/"partially", number of countries) - description: - - Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal
- - *count_no_description + description: | + Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -615,9 +667,10 @@ tables: numDecimalPlaces: 0 joint_adoption_no: title: Joint adoptions ("no"/"partially", number of countries) - description: - - Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such.
- - *count_no_description + description: | + Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -625,9 +678,10 @@ tables: numDecimalPlaces: 0 lgb_military_no: title: LGB military ("no"/"partially", number of countries) - description: - - Measures if lesbian, gay, and bisexual people are allowed to serve in the military.
- - *count_no_description + description: | + Measures if lesbian, gay, and bisexual people are allowed to serve in the military. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -635,9 +689,10 @@ tables: numDecimalPlaces: 0 lgb_military_ban_no: title: LGB military ban ("no"/"partially", number of countries) - description: - - Measures if lesbian, gay, and bisexual people are banned from the military.
- - *count_no_description + description: | + Measures if lesbian, gay, and bisexual people are banned from the military. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -645,9 +700,10 @@ tables: numDecimalPlaces: 0 marriage_equality_no: title: Marriage equality ("no"/"partially", number of countries) - description: - - Measures if there is no legal distinction between same-sex and different-sex marriages.
- - *count_no_description + description: | + Measures if there is no legal distinction between same-sex and different-sex marriages. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -655,9 +711,10 @@ tables: numDecimalPlaces: 0 marriage_ban_no: title: Ban on marriage equality ("no"/"partially", number of countries) - description: - - Measures if same-sex marriages are banned.
- - *count_no_description + description: | + Measures if same-sex marriages are banned. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -665,9 +722,10 @@ tables: numDecimalPlaces: 0 samesex_legal_no: title: Same-sex sexual acts legal ("no"/"partially", number of countries) - description: - - Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults.
- - *count_no_description + description: | + Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -675,9 +733,10 @@ tables: numDecimalPlaces: 0 third_gender_no: title: Third gender recognition ("no"/"partially", number of countries) - description: - - Measures if a third gender is recognized in the legislation.
- - *count_no_description + description: | + Measures if a third gender is recognized in the legislation. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -685,9 +744,10 @@ tables: numDecimalPlaces: 0 trans_military_no: title: Trasgender military ("no"/"partially", number of countries) - description: - - Measures if transgender people are allowed to serve in the military.
- - *count_no_description + description: | + Measures if transgender people are allowed to serve in the military. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -695,9 +755,10 @@ tables: numDecimalPlaces: 0 civil_unions_no: title: Civil unions ("no"/"partially", number of countries) - description: - - Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included.
- - *count_no_description + description: | + Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -705,9 +766,10 @@ tables: numDecimalPlaces: 0 gendermarker_no: title: Gender marker change ("no"/"partially", number of countries) - description: - - Measures if the gender marker can be legally changed.
- - *count_no_description + description: | + Measures if the gender marker can be legally changed. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -715,9 +777,10 @@ tables: numDecimalPlaces: 0 propaganda_no: title: Anti-propaganda laws ("no", number of countries) - description: - - Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”.
- - *count_no_description + description: | + Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”. + + {descriptions.count_no} short_unit: '' unit: '' display: @@ -725,9 +788,10 @@ tables: numDecimalPlaces: 0 equal_age_yes_pop: title: Equal age of consent ("yes", total population) - description: - - Measures the presence of a law defining the same age of consent between same-sex and different-sex partners.
- - *pop_yes_description + description: | + Measures the presence of a law defining the same age of consent between same-sex and different-sex partners. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -735,9 +799,10 @@ tables: numDecimalPlaces: 0 unequal_age_yes_pop: title: Unequal age of consent ("yes"/"partially", total population) - description: - - Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults.
- - *pop_yes_description + description: | + Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults. + + {descriptions.pop_yes} short_unit: "" unit: '' display: @@ -745,9 +810,9 @@ tables: numDecimalPlaces: 0 constitution_yes_pop: title: Constitutional protections against discrimination ("yes", total population) - description: + description: | - National constitutions are classified as protective against discrimination based on sexual orientation or gender identity if there is explicit language or if judicial cases have set legal precedent for such protections. - - *pop_yes_description + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -755,9 +820,10 @@ tables: numDecimalPlaces: 0 conversion_therapies_yes_pop: title: Ban on conversion therapies ("yes", total population) - description: - - Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery.
- - *pop_yes_description + description: | + Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -765,9 +831,10 @@ tables: numDecimalPlaces: 0 death_penalty_yes_pop: title: Death penalty for same-sex sexual acts ("yes"/"partially", total population) - description: - - Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death.
- - *pop_yes_description + description: | + Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -775,9 +842,10 @@ tables: numDecimalPlaces: 0 employment_discrim_yes_pop: title: Employment discrimination bans ("yes", total population) - description: - - Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity.
- - *pop_yes_description + description: | + Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -785,9 +853,10 @@ tables: numDecimalPlaces: 0 gender_surgery_yes_pop: title: Ban on gender assignment surgeries on children ("yes", total population) - description: - - Measures if bans on gender assignment surgeries on children are adopted.
- - *pop_yes_description + description: | + Measures if bans on gender assignment surgeries on children are adopted. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -795,9 +864,10 @@ tables: numDecimalPlaces: 0 hate_crimes_yes_pop: title: Hate crime protections ("yes", total population) - description: - - Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance.
- - *pop_yes_description + description: | + Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -805,9 +875,10 @@ tables: numDecimalPlaces: 0 incite_hate_yes_pop: title: Incitement to hatred ("yes", total population) - description: - - Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal
- - *pop_yes_description + description: | + Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -815,9 +886,10 @@ tables: numDecimalPlaces: 0 joint_adoption_yes_pop: title: Joint adoptions ("yes", total population) - description: - - Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such.
- - *pop_yes_description + description: | + Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -825,9 +897,10 @@ tables: numDecimalPlaces: 0 lgb_military_yes_pop: title: LGB military ("yes", total population) - description: - - Measures if lesbian, gay, and bisexual people are allowed to serve in the military.
- - *pop_yes_description + description: | + Measures if lesbian, gay, and bisexual people are allowed to serve in the military. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -835,9 +908,10 @@ tables: numDecimalPlaces: 0 lgb_military_ban_yes_pop: title: LGB military ban ("yes", total population) - description: - - Measures if lesbian, gay, and bisexual people are banned from the military.
- - *pop_yes_description + description: | + Measures if lesbian, gay, and bisexual people are banned from the military. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -845,9 +919,10 @@ tables: numDecimalPlaces: 0 marriage_equality_yes_pop: title: Marriage equality ("yes", total population) - description: - - Measures if there is no legal distinction between same-sex and different-sex marriages.
- - *pop_yes_description + description: | + Measures if there is no legal distinction between same-sex and different-sex marriages. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -855,9 +930,10 @@ tables: numDecimalPlaces: 0 marriage_ban_yes_pop: title: Ban on marriage equality ("yes", total population) - description: - - Measures if same-sex marriages are banned.
- - *pop_yes_description + description: | + Measures if same-sex marriages are banned. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -865,9 +941,10 @@ tables: numDecimalPlaces: 0 samesex_legal_yes_pop: title: Same-sex sexual acts legal ("yes", total population) - description: - - Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults.
- - *pop_yes_description + description: | + Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -875,9 +952,10 @@ tables: numDecimalPlaces: 0 third_gender_yes_pop: title: Third gender recognition ("yes", total population) - description: - - Measures if a third gender is recognized in the legislation.
- - *pop_yes_description + description: | + Measures if a third gender is recognized in the legislation. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -885,9 +963,10 @@ tables: numDecimalPlaces: 0 trans_military_yes_pop: title: Trasgender military ("yes", total population) - description: - - Measures if transgender people are allowed to serve in the military.
- - *pop_yes_description + description: | + Measures if transgender people are allowed to serve in the military. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -895,9 +974,10 @@ tables: numDecimalPlaces: 0 civil_unions_yes_pop: title: Civil unions ("yes", total population) - description: - - Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included.
- - *pop_yes_description + description: | + Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -905,9 +985,10 @@ tables: numDecimalPlaces: 0 gendermarker_yes_pop: title: Gender marker change ("yes", total population) - description: - - Measures if the gender marker can be legally changed.
- - *pop_yes_description + description: | + Measures if the gender marker can be legally changed. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -915,9 +996,10 @@ tables: numDecimalPlaces: 0 propaganda_yes_pop: title: Anti-propaganda laws ("yes"/"partially", total population) - description: - - Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”.
- - *pop_yes_description + description: | + Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”. + + {descriptions.pop_yes} short_unit: '' unit: '' display: @@ -925,9 +1007,10 @@ tables: numDecimalPlaces: 0 equal_age_no_pop: title: Equal age of consent ("no"/"partially", total population) - description: - - Measures the presence of a law defining the same age of consent between same-sex and different-sex partners.
- - *pop_no_description + description: | + Measures the presence of a law defining the same age of consent between same-sex and different-sex partners. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -935,9 +1018,10 @@ tables: numDecimalPlaces: 0 unequal_age_no_pop: title: Unequal age of consent ("no", total population) - description: - - Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults.
- - *pop_no_description + description: | + Measures the presence of a law outlawing different ages of consent between same-sex and different-sex partners, which serves as a tool to inhibit same-sex acts between consenting adults. + + {descriptions.pop_no} short_unit: "" unit: '' display: @@ -945,9 +1029,10 @@ tables: numDecimalPlaces: 0 constitution_no_pop: title: Constitutional protections against discrimination ("no"/"partially", total population) - description: - - National constitutions are classified as protective against discrimination based on sexual orientation or gender identity if there is explicit language or if judicial cases have set legal precedent for such protections. - - *pop_no_description + description: | + National constitutions are classified as protective against discrimination based on sexual orientation or gender identity if there is explicit language or if judicial cases have set legal precedent for such protections. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -955,9 +1040,10 @@ tables: numDecimalPlaces: 0 conversion_therapies_no_pop: title: Ban on conversion therapies ("no"/"partially", total population) - description: - - Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery.
- - *pop_no_description + description: | + Measures if bans on conversion therapies are adopted. Conversion therapies are those attempting to change a person’s sexual orientation or gender identity. They can entail counseling, drugging, electric shocks, castrations, or brain surgery. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -965,9 +1051,10 @@ tables: numDecimalPlaces: 0 death_penalty_no_pop: title: Death penalty for same-sex sexual acts ("no", total population) - description: - - Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death.
- - *pop_no_description + description: | + Measures the adoption of policies that allow for individuals caught engaging in same-sex acts to be punished by death. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -975,9 +1062,10 @@ tables: numDecimalPlaces: 0 employment_discrim_no_pop: title: Employment discrimination bans ("no"/"partially", total population) - description: - - Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity.
- - *pop_no_description + description: | + Measures the presence of legislation banning employers from discriminating on the basis of sexual orientation or gender identity. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -985,9 +1073,10 @@ tables: numDecimalPlaces: 0 gender_surgery_no_pop: title: Ban on gender assignment surgeries on children ("no"/"partially", total population) - description: - - Measures if bans on gender assignment surgeries on children are adopted.
- - *pop_no_description + description: | + Measures if bans on gender assignment surgeries on children are adopted. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -995,9 +1084,10 @@ tables: numDecimalPlaces: 0 hate_crimes_no_pop: title: Hate crime protections ("no"/"partially", total population) - description: - - Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance.
- - *pop_no_description + description: | + Measures the adoption of hate crime laws, which designate a crime against someone based based on sexual orientation or gender identity as an aggravating circumstance. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1005,9 +1095,10 @@ tables: numDecimalPlaces: 0 incite_hate_no_pop: title: Incitement to hatred ("no"/"partially", total population) - description: - - Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal
- - *pop_no_description + description: | + Measures the adoption of incitement to hatred protections, which is any act that could provoke a targeted crime illegal + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1015,9 +1106,10 @@ tables: numDecimalPlaces: 0 joint_adoption_no_pop: title: Joint adoptions ("no"/"partially", total population) - description: - - Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such.
- - *pop_no_description + description: | + Measures if joint adoption policy is adopted. This policy allows for same-sex partners to legally adopt a child, with both parents being recognized as such. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1025,9 +1117,10 @@ tables: numDecimalPlaces: 0 lgb_military_no_pop: title: LGB military ("no"/"partially", total population) - description: - - Measures if lesbian, gay, and bisexual people are allowed to serve in the military.
- - *pop_no_description + description: | + Measures if lesbian, gay, and bisexual people are allowed to serve in the military. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1035,9 +1128,10 @@ tables: numDecimalPlaces: 0 lgb_military_ban_no_pop: title: LGB military ban ("no"/"partially", total population) - description: - - Measures if lesbian, gay, and bisexual people are banned from the military.
- - *pop_no_description + description: | + Measures if lesbian, gay, and bisexual people are banned from the military. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1045,9 +1139,10 @@ tables: numDecimalPlaces: 0 marriage_equality_no_pop: title: Marriage equality ("no"/"partially", total population) - description: - - Measures if there is no legal distinction between same-sex and different-sex marriages.
- - *pop_no_description + description: | + Measures if there is no legal distinction between same-sex and different-sex marriages. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1055,9 +1150,10 @@ tables: numDecimalPlaces: 0 marriage_ban_no_pop: title: Ban on marriage equality ("no"/"partially", total population) - description: - - Measures if same-sex marriages are banned.
- - *pop_no_description + description: | + Measures if same-sex marriages are banned. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1065,9 +1161,10 @@ tables: numDecimalPlaces: 0 samesex_legal_no_pop: title: Same-sex sexual acts legal ("no"/"partially", total population) - description: - - Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults.
- - *pop_no_description + description: | + Measures the presence of a law declaring that same-sex actions are not criminalized between consenting adults. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1075,9 +1172,10 @@ tables: numDecimalPlaces: 0 third_gender_no_pop: title: Third gender recognition ("no"/"partially", total population) - description: - - Measures if a third gender is recognized in the legislation.
- - *pop_no_description + description: | + Measures if a third gender is recognized in the legislation. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1085,9 +1183,10 @@ tables: numDecimalPlaces: 0 trans_military_no_pop: title: Trasgender military ("no"/"partially", total population) - description: - - Measures if transgender people are allowed to serve in the military.
- - *pop_no_description + description: | + Measures if transgender people are allowed to serve in the military. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1095,9 +1194,10 @@ tables: numDecimalPlaces: 0 civil_unions_no_pop: title: Civil unions ("no"/"partially", total population) - description: - - Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included.
- - *pop_no_description + description: | + Measures if civil unions for same-sex partners are adopted. Domestic and registered partnerships are included. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1105,9 +1205,10 @@ tables: numDecimalPlaces: 0 gendermarker_no_pop: title: Gender marker change ("no"/"partially", total population) - description: - - Measures if the gender marker can be legally changed.
- - *pop_no_description + description: | + Measures if the gender marker can be legally changed. + + {descriptions.pop_no} short_unit: '' unit: '' display: @@ -1115,9 +1216,10 @@ tables: numDecimalPlaces: 0 propaganda_no_pop: title: Anti-propaganda laws ("no", total population) - description: - - Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”.
- - *pop_no_description + description: | + Measures the adoption of policies banning “propaganda for non-traditional sexual relations”. Vaguely written, these laws are utilized to discriminate against LGBT individuals in the name of protecting “public morality, particularly pertaining to children”. + + {descriptions.pop_no} short_unit: '' unit: '' display: diff --git a/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.py b/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.py index 3b9bcb0c453..80c317fe1e3 100644 --- a/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.py +++ b/etl/steps/data/garden/lgbt_rights/2023-04-27/lgbti_policy_index.py @@ -202,13 +202,6 @@ def run(dest_dir: str) -> None: # Create a new garden dataset with the same metadata as the meadow dataset. ds_garden = create_dataset(dest_dir, tables=[tb_garden]) - # For now the variable descriptions are stored as a list of strings, this transforms them into a single string - tb_garden = ds_garden["lgbti_policy_index"] - for col in tb_garden.columns: - if isinstance(tb_garden[col].metadata.description, list): - tb_garden[col].metadata.description = "\n".join(tb_garden[col].metadata.description) - ds_garden.add(tb_garden) - # Save changes in the new garden dataset. ds_garden.save() diff --git a/etl/steps/data/garden/lis/2023-01-18/luxembourg_income_study.meta.yml b/etl/steps/data/garden/lis/2023-01-18/luxembourg_income_study.meta.yml index 116b8013064..a686ebc4c92 100644 --- a/etl/steps/data/garden/lis/2023-01-18/luxembourg_income_study.meta.yml +++ b/etl/steps/data/garden/lis/2023-01-18/luxembourg_income_study.meta.yml @@ -9,44 +9,42 @@ dataset: Harmonized into a common framework, LIS datasets contain household- and person-level data on labor income, capital income, pensions, public social benefits (excl. pensions) and private transfers, as well as taxes and contributions, demography, employment, and expenditures. - Income variables + **Income variables** This dataset contains poverty, inequality and distributional statistics for four different types of income or consumption: - + * **Disposable household income**, which is total income minus taxes and social security contributions (available as \`dhi\` in the LIS dataset). Total income comprises income from labor, capital, pensions, public social benefits and private income. + * **Disposable household cash income**, which is disposable household income minus the total value of goods and services (fringe benefits, home production, in-kind benefits and transfers) (available as \`dhci\` in the LIS dataset). + * **Market income**, the sum of factor income (labor plus capital income), private income (private cash transfers and in-kind goods and services, not involving goverment) and private pensions (constructed in LIS as \`hifactor + hiprivate + hi33\`). + * **Total consumption**, including that stemming from goods and services that have been purchased by the household, and goods ans services that have not been purchased, but either given to the household from somebody else, or self-produced (available as \`hcexp\` in the LIS dataset). All households where any of these income/consumption variables is missing are excluded, except when data is not available for this variable in the entire survey (this happens for example with total consumption in several countries). - Gross and market income + **Gross and market income** LIS datasets are classified into either gross, net or mixed income datasets depending on the extent to which taxes and social security contributions is captured in the original data. This is essential for estimating market income, our LIS measure of income before tax. Consequently, market income is only estimated when taxes and contributions are fully captured, collected or imputed (codes 100, 110 and 120 for the `grossnet` variable). - Current income + **Current income** Income data from LIS is based on current income, which consists of cash and non-cash payments received by the household or by individual household members at periodic intervals. These include cash and in-kind income from labor, income from capital, pensions, cash payments from social security transfers (excluding pensions), and non-cash social assistance transfers, as well as cash and in-kind private transfers. Two types of income are excluded from this definition: non-cash incomes from capital (imputed value of items such as dwellings and cars) and in-kind universal transfers from the government (housing, care, education, health). - Consumption data in LIS + **Consumption data in LIS ** LIS records total consumption, including that stemming from expenditures (i.e. if the household has purchased the good or service consumed) and that stemming from own-production, transfers, or gifts (goods and values consumed and not purchased, but either given to the household from somebody else or self-produced). Data on total consumption has a lower coverage compared to income. - Equivalence scales + **Equivalence scales** For each of these types of income or consumption, equivalized and per capita measures are available. 'Equivalized' means that household income or consumption is divided by the LIS equivalence scale (squared root of the number of household members) to address for economies of scale in the household. 'Per capita' means that income or consumption is divided by the total number of household members. In both cases all members of a given household have the same equivalent income, regardless of age, gender, or relationship to the household head. - Top and bottom-coding + **Top and bottom-coding** Data is also top and bottom-coded. Before equivalization, top and bottom coding is applied by setting boundaries for extreme values of log transformed income or consumption variable: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. - Adjustments to total population + **Adjustments to total population** Person-level adjusted weights are used when generating income indicators for the total population. This means that survey data is adjusted to the population by multiplying the household weight by the number of household members (HWGT*NHHMEM). - Purchasing power parities + **Purchasing power parities** All LIS income and consumption variables are originally reported in annual amounts and in units of the national currency in use today. In Our World in Data, we use international-$ in 2017 prices to account for inflation and for differences in the cost of living between countries. LIS provides conversion tables in its platform. version: "2023-01-18" diff --git a/etl/steps/data/garden/lis/2023-01-18/shared.py b/etl/steps/data/garden/lis/2023-01-18/shared.py index 82cfa619109..57ebf0af3bd 100644 --- a/etl/steps/data/garden/lis/2023-01-18/shared.py +++ b/etl/steps/data/garden/lis/2023-01-18/shared.py @@ -5,27 +5,31 @@ from owid.catalog import Table, VariableMeta -# These is text common to all variables -new_line = "

" +# This is text common to all variables notes_title = "NOTES ON HOW WE PROCESSED THIS INDICATOR" -processing_description = new_line.join( - [ - "The Luxembourg Income Study data is created from standardized household survey microdata available in their LISSY platform. The estimations follow the methodology available in LIS, Key Figures and DART platform.", - "After tax income is obtained by using the disposable household income variable (dhi)", - "Before tax income is estimated by calculating the sum of income from labor and capital (variable hifactor), cash transfers and in-kind goods and services from privates (hiprivate) and private pensions (hi33). This is done only for surveys where tax and contributions are fully captured, collected or imputed.", - "After tax income (cash) is obtained using the disposable household cash income variable (dhci).", - "Consumption is obtained using the total consumption variable (hcexp).", - "Income data is converted from local currency into international-$ by dividing by the LIS PPP factor, available as an additional database in the system.", - "Incomes are top and bottom-coded by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.", - "Incomes are equivalized by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.", - ] -) - -processing_poverty = "Poverty indicators are obtained by using Stata’s povdeco function. Weights are set as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). The function generates FGT(0) and FGT(1), headcount ratio and poverty gap index. After extraction, further data processing steps are done to estimate other poverty indicators using these values, population and poverty lines for absolute and relative poverty." -processing_gini_mean_median = "Gini coefficients are obtained by using Stata’s ineqdec0 function. Weights are set as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). From this function, mean and median values are also calculated." -processing_distribution = "Income shares and thresholds by decile are obtained by using Stata’s sumdist function. The parameters set are again the weight (nhhmem*hwgt) and the number of quantile groups (10). Threshold ratios, share ratios and averages by decile are estimated after the use of LISSY with this data." +processing_description = """ + The Luxembourg Income Study data is created from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. + + After tax income is obtained by using the disposable household income variable (`dhi`) + + Before tax income is estimated by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). This is done only for surveys where tax and contributions are fully captured, collected or imputed. + + After tax income (cash) is obtained using the disposable household cash income variable (`dhci`). + + Consumption is obtained using the total consumption variable (`hcexp`). + + Income data is converted from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the system. + + Incomes are top and bottom-coded by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. + + Incomes are equivalized by dividing each household observation by the square root of the number of household members (`nhhmem`). Per capita estimates are calculated by dividing incomes by the number of household members. +""" + +processing_poverty = "Poverty indicators are obtained by using [Stata’s povdeco function](https://ideas.repec.org/c/boc/bocode/s366004.html). Weights are set as the product between the number of household members (`nhhmem`) and the normalized household weight (`hwgt`). The function generates FGT(0) and FGT(1), headcount ratio and poverty gap index. After extraction, further data processing steps are done to estimate other poverty indicators using these values, population and poverty lines for absolute and relative poverty." +processing_gini_mean_median = "Gini coefficients are obtained by using [Stata’s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). Weights are set as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). From this function, mean and median values are also calculated." +processing_distribution = "Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). The parameters set are again the weight (`nhhmem*hwgt`) and the number of quantile groups (10). Threshold ratios, share ratios and averages by decile are estimated after the use of LISSY with this data." ppp_description = "The data is measured in international-$ at 2017 prices – this adjusts for inflation and for differences in the cost of living between countries." @@ -326,17 +330,19 @@ def var_metadata_income_and_equivalence_scale(var, wel, e) -> VariableMeta: if var == "mean" or var == "median": meta = VariableMeta( title=f"{var_dict[var]['title']} ({inc_cons_dict[wel]['name']}, {equivalence_scales_dict[e]['name']})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - equivalence_scales_dict[e]["description"], - ppp_description, - notes_title, - processing_description, - processing_gini_mean_median, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {equivalence_scales_dict[e]['description']} + + {ppp_description} + + {notes_title} + + {processing_description} + + {processing_gini_mean_median}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -348,17 +354,19 @@ def var_metadata_income_and_equivalence_scale(var, wel, e) -> VariableMeta: else: meta = VariableMeta( title=f"{var_dict[var]['title']} ({inc_cons_dict[wel]['name']}, {equivalence_scales_dict[e]['name']})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - equivalence_scales_dict[e]["description"], - notes_title, - processing_description, - processing_gini_mean_median, - processing_distribution, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {equivalence_scales_dict[e]['description']} + + {notes_title} + + {processing_description} + + {processing_gini_mean_median} + + {processing_distribution}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -372,16 +380,17 @@ def var_metadata_income_and_equivalence_scale(var, wel, e) -> VariableMeta: def var_metadata_income_equivalence_scale_relative(var, wel, e, rel) -> VariableMeta: meta = VariableMeta( title=f"{rel_dict[rel]} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}, {equivalence_scales_dict[e]['name']})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - equivalence_scales_dict[e]["description"], - notes_title, - processing_description, - processing_poverty, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {equivalence_scales_dict[e]['description']} + + {notes_title} + + {processing_description} + + {processing_poverty}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -395,17 +404,19 @@ def var_metadata_income_equivalence_scale_relative(var, wel, e, rel) -> Variable def var_metadata_income_equivalence_scale_absolute(var, wel, e, abs) -> VariableMeta: meta = VariableMeta( title=f"{abs_dict[abs]} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}, {equivalence_scales_dict[e]['name']})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - equivalence_scales_dict[e]["description"], - ppp_description, - notes_title, - processing_description, - processing_poverty, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {equivalence_scales_dict[e]['description']} + + {ppp_description} + + {notes_title} + + {processing_description} + + {processing_poverty}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -420,17 +431,19 @@ def var_metadata_income_equivalence_scale_percentiles(var, wel, e, pct) -> Varia if var == "thr": meta = VariableMeta( title=f"{pct_dict[pct]['decile9']} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}, {equivalence_scales_dict[e]['name']})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - equivalence_scales_dict[e]["description"], - ppp_description, - notes_title, - processing_description, - processing_distribution, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {equivalence_scales_dict[e]['description']} + + {ppp_description} + + {notes_title} + + {processing_description} + + {processing_distribution}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -442,17 +455,19 @@ def var_metadata_income_equivalence_scale_percentiles(var, wel, e, pct) -> Varia elif var == "avg": meta = VariableMeta( title=f"{pct_dict[pct]['decile10']} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}, {equivalence_scales_dict[e]['name']})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - equivalence_scales_dict[e]["description"], - ppp_description, - notes_title, - processing_description, - processing_distribution, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {equivalence_scales_dict[e]['description']} + + {ppp_description} + + {notes_title} + + {processing_description} + + {processing_distribution}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -464,16 +479,17 @@ def var_metadata_income_equivalence_scale_percentiles(var, wel, e, pct) -> Varia else: meta = VariableMeta( title=f"{pct_dict[pct]['decile10']} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}, {equivalence_scales_dict[e]['name']})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - equivalence_scales_dict[e]["description"], - notes_title, - processing_description, - processing_distribution, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {equivalence_scales_dict[e]['description']} + + {notes_title} + + {processing_description} + + {processing_distribution}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) diff --git a/etl/steps/data/garden/oecd/2023-06-06/income_distribution_database.meta.yml b/etl/steps/data/garden/oecd/2023-06-06/income_distribution_database.meta.yml index 7c9d515ce2a..ab03f11dd24 100644 --- a/etl/steps/data/garden/oecd/2023-06-06/income_distribution_database.meta.yml +++ b/etl/steps/data/garden/oecd/2023-06-06/income_distribution_database.meta.yml @@ -10,7 +10,7 @@ descriptions: equivalization: |- Income has been equivalized – adjusted to account for the fact that people in the same household can share costs like rent and heating. additional_info: |- - The entire population of each country is considered, and also the income definition is the newest from the OECD since 2012. For more information on the methodology, visit the OECD Income Distribution Database (IDD) + The entire population of each country is considered, and also the income definition is the newest from the OECD since 2012. For more information on the methodology, visit the [OECD Income Distribution Database (IDD)](http://www.oecd.org/social/income-distribution-database.htm). covid: |- Survey estimates for 2020 are subject to additional uncertainty and are to be treated with extra caution, as in most countries the survey fieldwork was affected by the Coronavirus (COVID-19) pandemic. tables: diff --git a/etl/steps/data/garden/ophi/2022-12-13/multidimensional_poverty_index.meta.yml b/etl/steps/data/garden/ophi/2022-12-13/multidimensional_poverty_index.meta.yml index 6b872ae2265..a5d2c8f3456 100644 --- a/etl/steps/data/garden/ophi/2022-12-13/multidimensional_poverty_index.meta.yml +++ b/etl/steps/data/garden/ophi/2022-12-13/multidimensional_poverty_index.meta.yml @@ -6,14 +6,14 @@ dataset: description: | The global Multidimensional Poverty Index (MPI) is an international measure of acute multidimensional poverty covering over 100 developing countries. It complements traditional monetary poverty measures by capturing the acute deprivations in health, education, and living standards that a person faces simultaneously. -

How is multidimensional poverty defined?

+ #### How is multidimensional poverty defined? + Being ‘MPI poor’ means that a person is deprived in a third or more of ten indicators, grouped into three dimensions: - - Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the Years of schooling indicator if no household member has completed six years of schooling. A person is considered deprived in the Cooking fuel indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their methodological notes. + * **Health** – using two indicators: nutrition, child mortality + * **Education** – using two indicators: years of schooling, school attendance + * **Living standards** – using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets. + + Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the _Years of schooling_ indicator if no household member has completed six years of schooling. A person is considered deprived in the _Cooking fuel_ indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their [methodological notes](https://www.ophi.org.uk/wp-content/uploads/OPHI_MPI_MN_54_2022.pdf). The individual indicators are not ‘weighted’ equally: When adding up the number of indicators in which a person is deprived, some count for more than others. Health and education indicators are given a weight of 1/6, while the indicators within the living standards dimension are given a weight of 1/18. This means that the three dimensions – health, education and living standards – have an equal weight in the total of one-third each. @@ -35,14 +35,14 @@ dataset: definitions: - core: description: &description-core | -

How is multidimensional poverty defined?

+ #### How is multidimensional poverty defined? Being ‘MPI poor’ means that a person is deprived in a third or more of ten indicators, grouped into three dimensions: - - Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the Years of schooling indicator if no household member has completed six years of schooling. A person is considered deprived in the Cooking fuel indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their methodological notes. + + * **Health** – using two indicators: nutrition, child mortality + * **Education** – using two indicators: years of schooling, school attendance + * **Living standards** – using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets. + + Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the _Years of schooling_ indicator if no household member has completed six years of schooling. A person is considered deprived in the _Cooking fuel_ indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their [methodological notes](https://www.ophi.org.uk/wp-content/uploads/OPHI_MPI_MN_54_2022.pdf). The individual indicators are not ‘weighted’ equally: When adding up the number of indicators in which a person is deprived, some count for more than others. Health and education indicators are given a weight of 1/6, while the indicators within the living standards dimension are given a weight of 1/18. This means that the three dimensions – health, education and living standards – have an equal weight in the total of one-third each. @@ -60,10 +60,10 @@ dataset: 'Imagine two countries: in both, 30 percent of people are poor (incidence). Judged by this piece of information, these two countries are equally poor. However, imagine that in one of the two countries poor people are deprived—on average—in one-third of the dimensions, whereas in the other country, the poor are deprived—on average—in two-thirds. By combining the two pieces of information - the intensity of deprivations and the proportion of poor people - we know that these two countries are not equally poor, but rather that the second is poorer than the first because the intensity of poverty is higher.' - cme: description: &description-cme | - This variable is a current margin estimate (CME), based on the most recent survey data. Look for the harmonized over time (HOT) estimate to see trends over time. + *This variable is a current margin estimate (CME), based on the most recent survey data. Look for the harmonized over time (HOT) estimate to see trends over time.* - hot: description: &description-hot | - This variable is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimations comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data. + *This variable is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimations comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.* tables: multidimensional_poverty_index: diff --git a/etl/steps/data/garden/ophi/2023-07-05/multidimensional_poverty_index.meta.yml b/etl/steps/data/garden/ophi/2023-07-05/multidimensional_poverty_index.meta.yml index 805e06d21fd..6ac33b9cb1d 100644 --- a/etl/steps/data/garden/ophi/2023-07-05/multidimensional_poverty_index.meta.yml +++ b/etl/steps/data/garden/ophi/2023-07-05/multidimensional_poverty_index.meta.yml @@ -32,13 +32,15 @@ all_sources: definitions: core: |- -

How is multidimensional poverty defined?

+ #### How is multidimensional poverty defined? + Being ‘MPI poor’ means that a person is deprived in a third or more of ten indicators, grouped into three dimensions: - - Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the Years of schooling indicator if no household member has completed six years of schooling. A person is considered deprived in the Cooking fuel indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their methodological notes. + + * **Health** – using two indicators: nutrition, child mortality + * **Education** – using two indicators: years of schooling, school attendance + * **Living standards** – using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets. + + Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the _Years of schooling_ indicator if no household member has completed six years of schooling. A person is considered deprived in the _Cooking fuel_ indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their [methodological notes](https://www.ophi.org.uk/wp-content/uploads/OPHI_MPI_MN55_2023.pdf). The individual indicators are not ‘weighted’ equally: When adding up the number of indicators in which a person is deprived, some count for more than others. Health and education indicators are given a weight of 1/6, while the indicators within the living standards dimension are given a weight of 1/18. This means that the three dimensions – health, education and living standards – have an equal weight in the total of one-third each. @@ -52,9 +54,9 @@ definitions: 'Imagine two countries: in both, 30 percent of people are poor (incidence). Judged by this piece of information, these two countries are equally poor. However, imagine that in one of the two countries poor people are deprived—on average—in one-third of the dimensions, whereas in the other country, the poor are deprived—on average—in two-thirds. By combining the two pieces of information - the intensity of deprivations and the proportion of poor people - we know that these two countries are not equally poor, but rather that the second is poorer than the first because the intensity of poverty is higher.' cme: |- - This variable is a current margin estimate (CME), based on the most recent survey data. Look for the harmonized over time (HOT) estimate to see trends over time. + *This variable is a current margin estimate (CME), based on the most recent survey data. Look for the harmonized over time (HOT) estimate to see trends over time.* hot: |- - This variable is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimations comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data. + *This variable is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimations comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.* tables: multidimensional_poverty_index: @@ -482,4 +484,4 @@ tables: name: Intensity of multidimensional poverty (camp) numDecimalPlaces: 1 sources: - - *source-hot \ No newline at end of file + - *source-hot diff --git a/etl/steps/data/garden/owid/latest/key_indicators/key_indicators.meta.yml b/etl/steps/data/garden/owid/latest/key_indicators/key_indicators.meta.yml index eaa7c9d7a58..98776f3c15f 100644 --- a/etl/steps/data/garden/owid/latest/key_indicators/key_indicators.meta.yml +++ b/etl/steps/data/garden/owid/latest/key_indicators/key_indicators.meta.yml @@ -2,9 +2,9 @@ tables: population_density: title: Population density (World Bank, Gapminder, HYDE & UN) description: | - Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on three key sources: HYDE, Gapminder, and the UN World Population Prospects. This combines historical population estimates with median scenario projections to 2100. You can find more information on these sources and how our time series is constructed on this page: What sources do we rely on for population estimates? + Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on three key sources: HYDE, Gapminder, and the UN World Population Prospects. This combines historical population estimates with median scenario projections to 2100. You can find more information on these sources and how our time series is constructed on this page: [What sources do we rely on for population estimates?](https://ourworldindata.org/population-sources) - We combine this population dataset with the land area estimates published by the World Bank, to produce a long-run dataset of population density. + We combine this population dataset with the [land area estimates published by the World Bank](https://ourworldindata.org/grapher/land-area-km), to produce a long-run dataset of population density. In all sources that we rely on, population estimates and land area estimates are based on today's geographical borders. variables: @@ -17,7 +17,6 @@ tables: name: Population density unit: people per km² includeInTable: true - land_area: title: Land Area (FAO) description: | @@ -39,7 +38,7 @@ tables: name: Population includeInTable: true sources: - - name: Food and Agriculture Organization of the United Nations - published_by: World Bank - url: http://data.worldbank.org/data-catalog/world-development-indicators - date_accessed: 2021-08-08 + - name: Food and Agriculture Organization of the United Nations + published_by: World Bank + url: http://data.worldbank.org/data-catalog/world-development-indicators + date_accessed: 2021-08-08 diff --git a/etl/steps/data/garden/papers/2023-07-10/farmer_lafond_2016.meta.yml b/etl/steps/data/garden/papers/2023-07-10/farmer_lafond_2016.meta.yml index 862d725bea2..c2555848a4c 100644 --- a/etl/steps/data/garden/papers/2023-07-10/farmer_lafond_2016.meta.yml +++ b/etl/steps/data/garden/papers/2023-07-10/farmer_lafond_2016.meta.yml @@ -69,8 +69,7 @@ dataset: + Vinyl chloride is measured in 1966 USD/lbs. + Wind turbine (Denmark) is measured in DKK/kW. - According to Farmer & Lafond (2016), the data are mostly taken from the Santa-Fe Performance Curve DataBase, accessible at pcdb.santafe.edu. The database has been constructed from personal communications and from Colpier and Cornland (2002), Goldemberg et al. (2004), Lieberman (1984), Lipman and Sperling (1999), Zhao (1999), McDonald and Schrattenholzer (2001), Neij et al. (2003), Moore (2006), Nemet (2006), Schilling and Esmundo (2009). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from Koomey and Hultman (2007) and Cooper (2009). The DNA sequencing data is from Wetterstrand (2015) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. - + According to Farmer & Lafond (2016), the data are mostly taken from the [Santa-Fe Performance Curve DataBase](https://pcdb.santafe.edu/). The database has been constructed from personal communications and from [Colpier and Cornland (2002)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0095), [Goldemberg et al. (2004)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0130), [Lieberman (1984)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0180), [Lipman and Sperling (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0190), [Zhao (1999)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0310), [McDonald and Schrattenholzer (2001)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0205), [Neij et al. (2003)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0235), [Moore (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0215), [Nemet (2006)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0240), [Schilling and Esmundo (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0265). The data on photovoltaic prices has been collected from public releases of Strategies Unlimited, Navigant and SPV Market Research. The data on nuclear energy is from [Koomey and Hultman (2007)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0165) and [Cooper (2009)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0100). The DNA sequencing data is from [Wetterstrand (2015)](https://www.sciencedirect.com/science/article/pii/S0048733315001699#bib0290) (cost per human-size genome), and for each year the last available month (September for 2001-2002 and October afterwards) was taken and corrected for inflation using the US GDP deflator. tables: farmer_lafond_2016: variables: diff --git a/etl/steps/data/garden/rff/2022-10-11/emissions_weighted_carbon_price.meta.yml b/etl/steps/data/garden/rff/2022-10-11/emissions_weighted_carbon_price.meta.yml index 6a5c42ba695..f60c3b175f8 100644 --- a/etl/steps/data/garden/rff/2022-10-11/emissions_weighted_carbon_price.meta.yml +++ b/etl/steps/data/garden/rff/2022-10-11/emissions_weighted_carbon_price.meta.yml @@ -14,125 +14,124 @@ dataset: - Each sector’s contribution to a country’s CO2 emissions (e.g. what percentage of a country’s emissions come from electricity, or road transport) They then weight each sector’s carbon price by the relevant sector’s contribution to CO2 emissions, and aggregate these figures to get an economy-wide weighted carbon price. - A full technical note on this methodology is provided by the authors here. - + A full technical note on this methodology is provided by the authors [here](https://www.rff.org/publications/working-papers/emissions-weighted-carbon-price-sources-and-methods/). sources: - - - name: Dolphin, Pollitt and Newbery (2020). Emissions-weighted Carbon Price. - published_by: "Dolphin, G., Pollitt, M. and Newbery, D. 2020. The political economy of carbon pricing: a panel analysis. Oxford Economic Papers 72(2): 472-500." - publication_year: 2022 - publication_date: 2022-01-18 - url: https://github.com/g-dolphin/ECP - + - name: Dolphin, Pollitt and Newbery (2020). Emissions-weighted Carbon Price. + published_by: >- + Dolphin, G., Pollitt, M. and Newbery, D. 2020. The political economy of carbon pricing: a panel analysis. + Oxford Economic Papers 72(2): 472-500. + publication_year: 2022 + publication_date: 2022-01-18 + url: https://github.com/g-dolphin/ECP tables: emissions_weighted_carbon_price: title: Emissions-weighted carbon price variables: co2_with_ets_as_share_of_co2: title: CO2 emissions covered by an ETS as a share of the country's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_ets_as_share_of_ghg: title: CO2 emissions covered by an ETS as a share of the country's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_ets_as_share_of_world_co2: title: CO2 emissions covered by an ETS as a share of the world's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_ets_as_share_of_world_ghg: title: CO2 emissions covered by an ETS as a share of the world's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_co2: title: CO2 emissions covered by a carbon tax as a share of the country's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_ghg: title: CO2 emissions covered by a carbon tax as a share of the country's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_world_co2: title: CO2 emissions covered by a carbon tax as a share of the world's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_as_share_of_world_ghg: title: CO2 emissions covered by a carbon tax as a share of the world's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_co2: title: CO2 emissions covered by a carbon tax or an ETS as a share of the country's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_ghg: title: CO2 emissions covered by a carbon tax or an ETS as a share of the country's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_world_co2: title: CO2 emissions covered by a carbon tax or an ETS as a share of the world's CO2 emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 co2_with_tax_or_ets_as_share_of_world_ghg: title: CO2 emissions covered by a carbon tax or an ETS as a share of the world's GHG emissions - unit: "%" - short_unit: "%" + unit: '%' + short_unit: '%' display: numDecimalPlaces: 2 price_with_ets_weighted_by_share_of_co2: title: Average price on emissions covered by an ETS, weighted by the share of the country's CO2 emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_ets_weighted_by_share_of_ghg: title: Average price on emissions covered by an ETS, weighted by the share of the country's GHG emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_or_ets_weighted_by_share_of_co2: title: Average price on emissions covered by a carbon tax or an ETS, weighted by the share of the country's CO2 emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_or_ets_weighted_by_share_of_ghg: title: Average price on emissions covered by a carbon tax or an ETS, weighted by the share of the country's GHG emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_weighted_by_share_of_co2: title: Average price on emissions covered by a carbon tax, weighted by the share of the country's CO2 emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 price_with_tax_weighted_by_share_of_ghg: title: Average price on emissions covered by a carbon tax, weighted by the share of the country's GHG emissions - unit: "2019 US$ per tonne of carbon dioxide equivalents" - short_unit: "2019 US$/ tCO2e" + unit: 2019 US$ per tonne of carbon dioxide equivalents + short_unit: 2019 US$/ tCO2e display: numDecimalPlaces: 2 diff --git a/etl/steps/data/garden/usda_nass/2023-04-20/us_corn_yields.meta.yml b/etl/steps/data/garden/usda_nass/2023-04-20/us_corn_yields.meta.yml index e1dd71fb846..d1dfd607ecc 100644 --- a/etl/steps/data/garden/usda_nass/2023-04-20/us_corn_yields.meta.yml +++ b/etl/steps/data/garden/usda_nass/2023-04-20/us_corn_yields.meta.yml @@ -1,8 +1,7 @@ dataset: title: Long-term corn yields in United States (USDA/NASS, 2023) description: | - This data is sourced from the USDA/NASS database, which reports survey data on corn yields in bushels per acre. To convert these values to tonnes per hectare, we have used a conversion factor of 0.06276, following USDA definitions. - + This data is sourced from the USDA/NASS database, which reports survey data on corn yields in bushels per acre. To convert these values to tonnes per hectare, we have used a conversion factor of 0.06276, following [USDA definitions](https://www.ers.usda.gov/webdocs/publications/41880/33132_ah697_002.pdf). tables: us_corn_yields: variables: diff --git a/etl/steps/data/garden/who/2022-09-30/ghe.meta.yml b/etl/steps/data/garden/who/2022-09-30/ghe.meta.yml index 7af9de54c20..8052090a371 100644 --- a/etl/steps/data/garden/who/2022-09-30/ghe.meta.yml +++ b/etl/steps/data/garden/who/2022-09-30/ghe.meta.yml @@ -1,28 +1,28 @@ # (Inherited from meadow, remove if not different.) all_sources: - - source_testing: &sources - name: WHO, Global Health Estimates (2020) - published_by: World Health Organization (2020) - url: https://www.who.int/data/global-health-estimates - date_accessed: 2022-09-30 - publication_date: # Example: 2023-01-01 - publication_year: # (if publication_date is not given). Example: 2023 - # description: Source description. +- source_testing: &sources + name: WHO, Global Health Estimates (2020) + published_by: World Health Organization (2020) + url: https://www.who.int/data/global-health-estimates + date_accessed: 2022-09-30 + publication_date: # Example: 2023-01-01 + publication_year: # (if publication_date is not given). Example: 2023 + # description: Source description. dataset: title: Global Health Estimates - World Health Organization (2020) description: | WHO's Global Health Estimates (GHE) provide the latest available data on death and disability globally, by region and country, and by age, sex and cause. The latest updates include global, regional and country trends from 2000 to 2019 inclusive. By providing key insights on mortality and morbidity trends, these estimates are a powerful tool to support informed decision-making on health policy and resource allocation. - Methods: + **Methods:** WHO's Global Health Estimates present comprehensive and comparable time-series data from 2000 onwards for health-related indicators, including life expectancy, healthy life expectancy, mortality and morbidity, as well as burden of diseases at global, regional and country levels, disaggregated by age, sex and cause. They are produced using data from multiple consolidated sources, including national vital registration data, latest estimates from WHO technical programmes, United Nations partners and inter-agency groups, as well as the Global Burden of Disease and other scientific studies. A broad spectrum of robust and  well-established scientific methods were applied for the processing, synthesis and analysis of data.  licenses: - - name: CC BY-NC-SA 3.0 IGO - url: https://www.who.int/about/policies/publishing/copyright + - name: CC BY-NC-SA 3.0 IGO + url: https://www.who.int/about/policies/publishing/copyright sources: - - *sources + - *sources tables: ghe: @@ -32,7 +32,7 @@ tables: description: | Number of deaths for a given cause. All the different causes can be found in Annex Table A at https://cdn.who.int/media/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf?sfvrsn=37bcfacc_5. unit: deaths - short_unit: "" + short_unit: '' display: name: Deaths numDecimalPlaces: 0 @@ -41,49 +41,47 @@ tables: description: | Death rate (per 100,000 people) for a given cause. All the different causes can be found in Annex Table A at https://cdn.who.int/media/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf?sfvrsn=37bcfacc_5. unit: deaths per 100,000 people - short_unit: "" + short_unit: '' display: name: Deaths per 100k numDecimalPlaces: 1 daly_count: title: The number of Disability Adjusted Life Yeats (DALYs) lost description: | - Rationale: + **Rationale:** Mortality does not give a complete picture of the burden of disease borne by individuals in different populations. The overall burden of disease is assessed using the disability-adjusted life year (DALY), a time-based measure that combines years of life lost due to premature mortality (YLLs) and years of life lost due to time lived in states of less than full health, or years of healthy life lost due to disability (YLDs). One DALY represents the loss of the equivalent of one year of full health. Using DALYs, the burden of diseases that cause premature death but little disability (such as drowning or measles) can be compared to that of diseases that do not cause death but do cause disability (such as cataract causing blindness). - Definition: + **Definition:** DALYs expressed per 100 000 population. DALYs for a disease or health condition are the sum of the years of life lost to due to premature mortality (YLLs) and the years lived with a disability (YLDs) due to prevalent cases of the disease or health condition in a population. - Method of estimation: + **Method of estimation:** DALYs expressed per 100 000 population. DALYs for a specific cause are calculated as the sum of the years of life lost due to premature mortality (YLLs) from that cause and the years of years of healthy life lost due to disability (YLDs) for people living in states of less than good health resulting from the specific cause. The YLLs for a cause are calculated as the number of cause-specific deaths multiplied by a loss function specifying the years lost for deaths as a function of the age at which death occurs. The loss function is based on the frontier national life expectancy projected for the year 2050 by the World Population Prospects 2012 (UN Population Division, 2013), with a life expectancy at birth of 92 years. Prevalence YLDs are used here. Prevalence YLDs are calculated as the prevalence of each non-fatal condition multiplied by its disability weight. More detailed method of estimation is available at: http://www.who.int/entity/healthinfo/statistics/GlobalDALYmethods_2000_2011.pdf?ua=1 - unit: DALYs - short_unit: "" + short_unit: '' display: name: Disability adjusted life years numDecimalPlaces: 2 daly_rate100k: title: DALYs per 100,000 people description: | - Rationale: + **Rationale:** Mortality does not give a complete picture of the burden of disease borne by individuals in different populations. The overall burden of disease is assessed using the disability-adjusted life year (DALY), a time-based measure that combines years of life lost due to premature mortality (YLLs) and years of life lost due to time lived in states of less than full health, or years of healthy life lost due to disability (YLDs). One DALY represents the loss of the equivalent of one year of full health. Using DALYs, the burden of diseases that cause premature death but little disability (such as drowning or measles) can be compared to that of diseases that do not cause death but do cause disability (such as cataract causing blindness). - Definition: + **Definition:** DALYs expressed per 100 000 population. DALYs for a disease or health condition are the sum of the years of life lost to due to premature mortality (YLLs) and the years lived with a disability (YLDs) due to prevalent cases of the disease or health condition in a population. - Method of estimation: + **Method of estimation:** DALYs expressed per 100 000 population. DALYs for a specific cause are calculated as the sum of the years of life lost due to premature mortality (YLLs) from that cause and the years of years of healthy life lost due to disability (YLDs) for people living in states of less than good health resulting from the specific cause. The YLLs for a cause are calculated as the number of cause-specific deaths multiplied by a loss function specifying the years lost for deaths as a function of the age at which death occurs. The loss function is based on the frontier national life expectancy projected for the year 2050 by the World Population Prospects 2012 (UN Population Division, 2013), with a life expectancy at birth of 92 years. Prevalence YLDs are used here. Prevalence YLDs are calculated as the prevalence of each non-fatal condition multiplied by its disability weight. More detailed method of estimation is available at: http://www.who.int/entity/healthinfo/statistics/GlobalDALYmethods_2000_2011.pdf?ua=1 - unit: DALYs per 100,000 people - short_unit: "" + short_unit: '' display: name: Disability adjusted life years per 100k numDecimalPlaces: 1 diff --git a/etl/steps/data/garden/wid/2023-01-27/shared.py b/etl/steps/data/garden/wid/2023-01-27/shared.py index 93e2770eb29..6255013d66e 100644 --- a/etl/steps/data/garden/wid/2023-01-27/shared.py +++ b/etl/steps/data/garden/wid/2023-01-27/shared.py @@ -7,14 +7,10 @@ # This is text common to all variables -new_line = "

" - -additional_description = new_line.join( - [ - "The data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.", - "These underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries.", - ] -) +additional_description = """ + The data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone. + These underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. + """ # NOTE: Change the year when needed ppp_description = "The data is measured in international-$ at 2022 prices – this adjusts for inflation and for differences in the cost of living between countries." @@ -279,14 +275,13 @@ def var_metadata_income(var, wel, ext) -> VariableMeta: if var == "p0p100_avg" or var == "median": meta = VariableMeta( title=f"{var_dict[var]['title']} ({inc_cons_dict[wel]['name']}) ({extrapolation_dict[ext]})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - ppp_description, - additional_description, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {ppp_description} + + {additional_description}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -298,9 +293,11 @@ def var_metadata_income(var, wel, ext) -> VariableMeta: else: meta = VariableMeta( title=f"{var_dict[var]['title']} ({inc_cons_dict[wel]['name']}) ({extrapolation_dict[ext]})", - description=new_line.join( - [var_dict[var]["description"], inc_cons_dict[wel]["description"], additional_description] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {additional_description}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -316,14 +313,13 @@ def var_metadata_income_percentiles(var, wel, pct, ext) -> VariableMeta: if var == "thr": meta = VariableMeta( title=f"{pct_dict[pct]['decile9']} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}) ({extrapolation_dict[ext]})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - ppp_description, - additional_description, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {ppp_description} + + {additional_description}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -335,14 +331,13 @@ def var_metadata_income_percentiles(var, wel, pct, ext) -> VariableMeta: elif var == "avg": meta = VariableMeta( title=f"{pct_dict[pct]['decile10']} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}) ({extrapolation_dict[ext]})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - ppp_description, - additional_description, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {ppp_description} + + {additional_description}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) @@ -355,13 +350,11 @@ def var_metadata_income_percentiles(var, wel, pct, ext) -> VariableMeta: else: meta = VariableMeta( title=f"{pct_dict[pct]['decile10']} - {var_dict[var]['title']} ({inc_cons_dict[wel]['name']}) ({extrapolation_dict[ext]})", - description=new_line.join( - [ - var_dict[var]["description"], - inc_cons_dict[wel]["description"], - additional_description, - ] - ), + description=f"""{var_dict[var]['description']} + + {inc_cons_dict[wel]['description']} + + {additional_description}""", unit=var_dict[var]["unit"], short_unit=var_dict[var]["short_unit"], ) diff --git a/etl/steps/data/garden/wid/2023-01-27/world_inequality_database.meta.yml b/etl/steps/data/garden/wid/2023-01-27/world_inequality_database.meta.yml index 91ff4101966..7cd747ab063 100644 --- a/etl/steps/data/garden/wid/2023-01-27/world_inequality_database.meta.yml +++ b/etl/steps/data/garden/wid/2023-01-27/world_inequality_database.meta.yml @@ -31,6 +31,7 @@ dataset: ### Measures of the distribution In WID’s view, to focus on a single indicator — for example the well-known Gini coefficient — is not sufficient to provide an adequate picture of inequality. WID stresses that the problem is not specifically about the Gini, or about any other indicator. The problem is that inequality cannot be reduced to a single number. This is why they prefer to describe distributions in their entirety, and then let users use whatever level of detail and whatever indicator suits their needs. In terms of presenting the results, WID favors showing the income shares of three main groups (the bottom 50%, the middle 40% and the top 10%). These three groups map relatively well to the idea of a lower, middle and upper class. They summarize changes happening to the overall distribution fairly well. In practice, synthetic indicators can be approximated quite precisely by a weighted average of these three shares. WID also emphasizes using the very top groups (top 1%, top 0.1%, etc.) since they can represent a macroeconomically significant share of income and wealth. Gini coefficients are provided in the database as a convenience but encourage users to look further. WID provides distributional data by generating synthetic microfiles (synthetic microdata representative of the distribution of income and wealth for the entire population) and summarizing it in generalized percentiles, which are series with thresholds, averages and shares for 127 fractiles: + - 99 percentiles from p = 0% to p = 99%, - 9 tenths of a percentile from p = 99% to p = 99.9%, - 9 hundredths of a percentile from p = 99.9% to p = 99.99%, @@ -41,6 +42,7 @@ dataset: DINA income series distribute the entirety of net national income using concepts that are consistent with the SNA. Therefore, they include certain types of income (like the undistributed profits of corporations or indirect taxes) that are traditionally overlooked by other sources. WID defines four broad types of series: + - **Pretax factor** corresponds to the distribution of income before any redistribution, be it through social insurance systems of social assistance. - **Pretax post-replacement income** (often referred to as “pretax income”) includes redistribution that occurs through social insurance schemes (pension and sometimes unemployment benefits), but not social assistance. The main difference with pretax factor income and is the treatment of pensions, which are counted on a contribution basis by pretax factor income and on a distribution basis by pretax national income. The key reason “pretax national income” series is preferred is that it is less sensitive than pretax factor income inequality to the age structure of the population. - **Post-tax disposable income** includes all cash redistribution through the tax and transfer system, but does not include in-kind benefits and therefore does not add up to national income. @@ -64,6 +66,7 @@ dataset: ### When tax data is limited In countries where the tax data is too limited (because they only provide tax tabulations or because the informal sector is too large), WID uses the tax data to correct the surveys at the top using the approach of Blanchet, Flores, and Morgan (2019). The motive for doing so is that surveys tend to underrepresent high incomes as compared to what appears in register data. This is even more true when the survey has not been matched to administrative records (e.g., social security data on wages). The arbitrary brackets used in tax tabulations are interpolated using the generalized Pareto interpolation method, known as gpinter, which allows the distribution to have a flexible form. The method to incorporate tax information into surveys has three stages: + - The choice of the merging point: the highest income where the ratio of the density functions of both survey and tax records coincides with the respective ratio of cumulative density functions. - The reweighting of survey observations above and below this point: below are uniformly reweighted (assuming relative probability of response constant over this part of the distribution). - The expansion of the survey’s support by including the highest incomes from tax data: after the merging point the survey distribution is replaced by the tax distribution. @@ -71,14 +74,14 @@ dataset: Finally, income components are rescaled to SNA aggregates. Several levels of aggregation may be used depending on the quality and the precision of the data. More information is available at https://wid.world/methodology/ - version: "2023-01-27" + version: '2023-01-27' sources: - - name: World Inequality Database (WID.world) (2023) - url: https://wid.world/ - date_accessed: "2023-06-12" - publication_year: 2023 - published_by: World Inequality Database (WID), https://wid.world - description: Data comes from national income surveys, tax records and national accounts + - name: World Inequality Database (WID.world) (2023) + url: https://wid.world/ + date_accessed: '2023-06-12' + publication_year: 2023 + published_by: World Inequality Database (WID), https://wid.world + description: Data comes from national income surveys, tax records and national accounts tables: world_inequality_database: variables: {} diff --git a/etl/steps/data/meadow/ophi/2022-12-13/multidimensional_poverty_index.meta.yml b/etl/steps/data/meadow/ophi/2022-12-13/multidimensional_poverty_index.meta.yml index 4b10e1e222f..607b3ab3b71 100644 --- a/etl/steps/data/meadow/ophi/2022-12-13/multidimensional_poverty_index.meta.yml +++ b/etl/steps/data/meadow/ophi/2022-12-13/multidimensional_poverty_index.meta.yml @@ -6,14 +6,16 @@ dataset: description: | The global Multidimensional Poverty Index (MPI) is an international measure of acute multidimensional poverty covering over 100 developing countries. It complements traditional monetary poverty measures by capturing the acute deprivations in health, education, and living standards that a person faces simultaneously. -

How is multidimensional poverty defined?

+ #### How is multidimensional poverty defined? + Being ‘MPI poor’ means that a person is deprived in a third or more of ten indicators, grouped into three dimensions: - - Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the Years of schooling indicator if no household member has completed six years of schooling. A person is considered deprived in the Cooking fuel indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their methodological notes. + + * **Health** – using two indicators: nutrition, child mortality + * **Education** – using two indicators: years of schooling, school attendance + * **Living standards** – using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets. + + + Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the *Years of schooling* indicator if no household member has completed six years of schooling. A person is considered deprived in the *Cooking fuel* indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their [methodological notes](https://www.ophi.org.uk/wp-content/uploads/OPHI_MPI_MN_54_2022.pdf). The individual indicators are not ‘weighted’ equally: When adding up the number of indicators in which a person is deprived, some count for more than others. Health and education indicators are given a weight of 1/6, while the indicators within the living standards dimension are given a weight of 1/18. This means that the three dimensions – health, education and living standards – have an equal weight in the total of one-third each. @@ -21,12 +23,13 @@ dataset: The global MPI was developed by OPHI with the UN Development Programme (UNDP) for inclusion in UNDP’s flagship Human Development Report in 2010. It has been published annually by OPHI and in the HDRs ever since. sources: - - - name: Alkire, Kanagaratnam and Suppa (2022), The global Multidimensional Poverty Index (MPI) 2022 - published_by: Alkire, S., Kanagaratnam, U., and Suppa, N. (2022). ‘The global Multidimensional Poverty Index (MPI) 2022 country results and methodological note’, OPHI MPI Methodological Note 52, Oxford Poverty and Human Development Initiative, University of Oxford. - publication_year: 2022 - date_accessed: 2022-10-26 - url: https://ophi.org.uk/multidimensional-poverty-index/ + - name: Alkire, Kanagaratnam and Suppa (2022), The global Multidimensional Poverty Index (MPI) 2022 + published_by: "Alkire, S., Kanagaratnam, U., and Suppa, N. (2022). 'The global Multidimensional Poverty Index (MPI) + 2022 country results and methodological note', OPHI MPI Methodological Note 52, Oxford Poverty and Human Development + Initiative, University of Oxford." + publication_year: 2022 + date_accessed: 2022-10-26 + url: https://ophi.org.uk/multidimensional-poverty-index/ tables: multidimensional_poverty_index: variables: @@ -73,16 +76,14 @@ tables: description: | Code of indicator (missing if aggregate measure). The options are: - + * **M0** – MPI (adjusted headcount ratio) + * **H** – Headcount ratio (proportion of population which is MPI poor) + * **A** – Intensity (average deprivation among the poor) + * **hd** – Uncensored deprivation rate (proportion of people deprived in indicator) + * **hdk** – Censored deprivation rate (proportion of people being poor and deprived in indicator) + * **actb** – Absolute contribution (Absolute contribution of indicator to MPI) + * **pctb** – Percentage contribution (Relative contribution of indicator to MPI) + * **popsh** – Population share of particular subgroup (if applicable) ind_lab: title: Indicator (human-readable) description: | diff --git a/lib/walden/ingests/papers/2022-11-01/zijdeman_et_al_2015/meta.yml b/lib/walden/ingests/papers/2022-11-01/zijdeman_et_al_2015/meta.yml index 7424bc8613c..10c0d12d9fd 100644 --- a/lib/walden/ingests/papers/2022-11-01/zijdeman_et_al_2015/meta.yml +++ b/lib/walden/ingests/papers/2022-11-01/zijdeman_et_al_2015/meta.yml @@ -11,18 +11,18 @@ license_name: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication License publication_year: 2015 description: | This dataset provides Period Life Expectancy at birth per country and year. The overall aim of the dataset is to cover the entire world for the period 1500-2000. - The current version (version 2) was build as part of the OECD "How was life" project. The dataset has nearly global coverage for the post 1950 period, while pre + The current version (version 2) was build as part of the OECD "How was life" project. The dataset has nearly global coverage for the post 1950 period, while pre 1950 the coverage decreases the more historic the time period. Depending on sources, the data are annual estimates, 5 yearly or decadel estimates The sources used are: - - UN World Population Project. - - http://www.mortality.org. - - http://www.gapminder.org. - - http://stats.oecd.org. - - Montevideo-Oxford Latin America Economic History Database. - - http://www.ons.gov.uk/ons/datasets-and-tables/index.html. - - http://www.abs.gov.au/ausstats/abs@.nsf/web+pages/statistics?opendocument#from-banner=LN. + - [UN World Population Project](http://esa.un.org/wpp/). + - [http://www.mortality.org](Human Mortality Database). + - [http://www.gapminder.org](Gapminder). + - [http://stats.oecd.org](OECD). + - [Montevideo-Oxford Latin America Economic History Database](http://www.lac.ox.ac.uk/moxlad-database). + - [http://www.ons.gov.uk/ons/datasets-and-tables/index.html](ONS). + - [http://www.abs.gov.au/ausstats/abs@.nsf/web+pages/statistics?opendocument#from-banner=LN](Australian Bureau of Statistics). - Kannisto, V., Nieminen, M. & Turpeinen, O. (1999). Finnish Life Tables since 1751, Demographic Research, 1(1), DOI: 10.4054/DemRes.1999.1.1 For specifics concerning (selections of) the sources, see the R-file below, with which the dataset was created. diff --git a/snapshots/ophi/2022-12-13/multidimensional_poverty_index.csv.dvc b/snapshots/ophi/2022-12-13/multidimensional_poverty_index.csv.dvc index c101364cc7f..5cb5edc6d70 100644 --- a/snapshots/ophi/2022-12-13/multidimensional_poverty_index.csv.dvc +++ b/snapshots/ophi/2022-12-13/multidimensional_poverty_index.csv.dvc @@ -16,14 +16,14 @@ meta: description: | The global Multidimensional Poverty Index (MPI) is an international measure of acute multidimensional poverty covering over 100 developing countries. It complements traditional monetary poverty measures by capturing the acute deprivations in health, education, and living standards that a person faces simultaneously. -

How is multidimensional poverty defined?

+ #### How is multidimensional poverty defined? Being ‘MPI poor’ means that a person is deprived in a third or more of ten indicators, grouped into three dimensions: - - Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the Years of schooling indicator if no household member has completed six years of schooling. A person is considered deprived in the Cooking fuel indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their methodological notes. + + - **Health** – using two indicators: nutrition, child mortality + - **Education** – using two indicators: years of schooling, school attendance + - **Living standards** – using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets. + + Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the _Years of schooling_ indicator if no household member has completed six years of schooling. A person is considered deprived in the _Cooking fuel_ indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their [methodological notes](https://www.ophi.org.uk/wp-content/uploads/OPHI_MPI_MN_54_2022.pdf). The individual indicators are not ‘weighted’ equally: When adding up the number of indicators in which a person is deprived, some count for more than others. Health and education indicators are given a weight of 1/6, while the indicators within the living standards dimension are given a weight of 1/18. This means that the three dimensions – health, education and living standards – have an equal weight in the total of one-third each. diff --git a/snapshots/ophi/2023-07-05/multidimensional_poverty_index.csv.dvc b/snapshots/ophi/2023-07-05/multidimensional_poverty_index.csv.dvc index e2733b537d6..81a5446ad5c 100644 --- a/snapshots/ophi/2023-07-05/multidimensional_poverty_index.csv.dvc +++ b/snapshots/ophi/2023-07-05/multidimensional_poverty_index.csv.dvc @@ -14,13 +14,14 @@ meta: description: | The global Multidimensional Poverty Index (MPI) is an international measure of acute multidimensional poverty covering over 100 developing countries. It complements traditional monetary poverty measures by capturing the acute deprivations in health, education, and living standards that a person faces simultaneously. -

How is multidimensional poverty defined?

+ #### How is multidimensional poverty defined? Being ‘MPI poor’ means that a person is deprived in a third or more of ten indicators, grouped into three dimensions: - - Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the Years of schooling indicator if no household member has completed six years of schooling. A person is considered deprived in the Cooking fuel indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their methodological notes. + + - **Health** – using two indicators: nutrition, child mortality + - **Education** – using two indicators: years of schooling, school attendance + - **Living standards** – using five indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets. + + Households are assessed as being deprived in a given indicator if they do not meet a certain threshold for that indicator. For instance, a household is deprived in the _Years of schooling_ indicator if no household member has completed six years of schooling. A person is considered deprived in the _Cooking fuel_ indicator if they cook using solid fuel, such as dung, agricultural crops, wood, charcoal, or coal. The thresholds for each indicator are published by OPHI in their [methodological notes](https://www.ophi.org.uk/wp-content/uploads/OPHI_MPI_MN55_2023.pdf). The individual indicators are not ‘weighted’ equally: When adding up the number of indicators in which a person is deprived, some count for more than others. Health and education indicators are given a weight of 1/6, while the indicators within the living standards dimension are given a weight of 1/18. This means that the three dimensions – health, education and living standards – have an equal weight in the total of one-third each. diff --git a/snapshots/wvs/2023-03-08/wvs_trust.csv.dvc b/snapshots/wvs/2023-03-08/wvs_trust.csv.dvc index 9b064bf6fca..ea6ecdcb1f2 100644 --- a/snapshots/wvs/2023-03-08/wvs_trust.csv.dvc +++ b/snapshots/wvs/2023-03-08/wvs_trust.csv.dvc @@ -22,32 +22,32 @@ meta: The World Values Survey (WVS) is an international research program devoted to the scientific and academic study of social, political, economic, religious and cultural values of people in the world. The main research instrument of the project is a representative comparative social survey conducted globally every five years. In the Our World in Data dataset we calculate national totals for the following questions: - + + - Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people? + - Could you tell me whether you trust people from you meet for the first time completely, somewhat, not very much or not at all? + - Could you tell me whether you trust people you know personally completely, somewhat, not very much or not at all? + - Do you think most people try to take advantage of you? + - Could you tell me whether you trust people in your family completely, somewhat, not very much or not at all? + - Could you tell me whether you trust people in your neighborhood completely, somewhat, not very much or not at all? + - Could you tell me whether you trust people of another religion completely, somewhat, not very much or not at all? + - Could you tell me whether you trust people of another nationality completely, somewhat, not very much or not at all? Additionally, we include national totals for confidence questions about organizations such as: - + + - Government + - Churches + - Armed forces + - Police + - Justice system + - Political parties + - Parliament + - Trade unions + - Universities + - Television + - Press + - Social movements, such as the women's movement or the environmental protection movement + - Regional organizations + - International organizations, such as United Nations, World Bank, the IMF The WVS runs a new survey wave every five years; the last update was done in 2022. We will aim to update our data on Our World in Data soon after the WVS updates the source data with a new wave. You can access the source page at the link above and see the latest available data from the WVS. wdir: ../../../data/snapshots/wvs/2023-03-08