update catalog

catalog/forecasts/Aquatics/Daily_Chlorophyll_a/collection.json

@@ -183,11 +183,7 @@
       "interval": [
         [
           "2023-01-01T00:00:00Z",
-<<<<<<< HEAD
           "2024-01-10T00:00:00Z"
-=======
-          "2024-01-09T00:00:00Z"
->>>>>>> 97a9410ae26143f721542ee168dffa6c1ef4cef1
         ]
       ]
     }
@@ -256,13 +252,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "pending",

catalog/forecasts/Aquatics/Daily_Dissolved_oxygen/collection.json

@@ -163,11 +163,7 @@
       "interval": [
         [
           "2023-01-01T00:00:00Z",
-<<<<<<< HEAD
           "2024-10-30T00:00:00Z"
-=======
-          "2024-10-29T00:00:00Z"
->>>>>>> 97a9410ae26143f721542ee168dffa6c1ef4cef1
         ]
       ]
     }
@@ -236,13 +232,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=oxygen?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=oxygen?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=oxygen?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=oxygen?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "pending",

catalog/forecasts/Aquatics/Daily_Water_temperature/collection.json

@@ -233,11 +233,7 @@
       "interval": [
         [
           "2023-01-01T00:00:00Z",
-<<<<<<< HEAD
           "2024-10-30T00:00:00Z"
-=======
-          "2024-10-29T00:00:00Z"
->>>>>>> 97a9410ae26143f721542ee168dffa6c1ef4cef1
         ]
       ]
     }
@@ -306,13 +302,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=temperature?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=temperature?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=temperature?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=temperature?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "pending",

catalog/forecasts/Aquatics/collection.json

@@ -137,13 +137,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |>\n dplyr::filter(variable %in% c(\"oxygen\", \"temperature\", \"chla\")) |>\n dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |>\n dplyr::filter(variable %in% c(\"oxygen\", \"temperature\", \"chla\")) |>\n dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "https://projects.ecoforecast.org/neon4cast-catalog/img/neon_buoy.jpg",

catalog/forecasts/Beetles/Weekly_beetle_community_abundance/collection.json

@@ -197,13 +197,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=abundance?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=abundance?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=abundance?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=abundance?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "pending",

catalog/forecasts/Beetles/Weekly_beetle_community_richness/collection.json

@@ -197,13 +197,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=richness?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=richness?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=richness?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=richness?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "pending",

catalog/forecasts/Beetles/collection.json

@@ -132,13 +132,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |>\n dplyr::filter(variable %in% c(\"abundance\", \"richness\")) |>\n dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |>\n dplyr::filter(variable %in% c(\"abundance\", \"richness\")) |>\n dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "https://www.neonscience.org/sites/default/files/styles/max_width_1170px/public/image-content-images/Beetles_pinned.jpg",

catalog/forecasts/Phenology/Daily_Green_chromatic_coordinate/collection.json

@@ -138,11 +138,7 @@
       "interval": [
         [
           "2023-01-01T00:00:00Z",
-<<<<<<< HEAD
           "2024-01-10T00:00:00Z"
-=======
-          "2024-01-09T00:00:00Z"
->>>>>>> 97a9410ae26143f721542ee168dffa6c1ef4cef1
         ]
       ]
     }
@@ -211,13 +207,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=gcc_90?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=gcc_90?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=gcc_90?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=gcc_90?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "pending",

catalog/forecasts/Phenology/Daily_Red_chromatic_coordinate/collection.json

@@ -153,11 +153,7 @@
       "interval": [
         [
           "2023-01-01T00:00:00Z",
-<<<<<<< HEAD
           "2024-01-10T00:00:00Z"
-=======
-          "2024-01-09T00:00:00Z"
->>>>>>> 97a9410ae26143f721542ee168dffa6c1ef4cef1
         ]
       ]
     }
@@ -226,13 +222,13 @@
   ],
   "assets": {
     "data": {
-      "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=rcc_90?endpoint_override=sdsc.osn.xsede.org",
+      "href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=rcc_90?endpoint_override=sdsc.osn.xsede.org\"",
       "type": "application/x-parquet",
       "title": "Database Access",
       "roles": [
         "data"
       ],
-      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=rcc_90?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
+      "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1D/variable=rcc_90?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n       \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
     },
     "thumbnail": {
       "href": "pending",