From 051b223b0a4392677a1c2418b95a65702ec2a6f8 Mon Sep 17 00:00:00 2001 From: Heinz-Alexander Fuetterer Date: Sat, 30 Sep 2023 12:44:08 +0200 Subject: [PATCH] docs: update readme (e.g. typos, markup) --- README.md | 53 ++++++++++++++++++++++++----------------------------- 1 file changed, 24 insertions(+), 29 deletions(-) diff --git a/README.md b/README.md index f22a7203..631059f1 100644 --- a/README.md +++ b/README.md @@ -8,8 +8,8 @@ Developers: [Robert Huber](mailto:rhuber@marum.de), [Anusuriya Devaraju](mailto: ## Overview -F-UJI is a web service to programatically assess FAIRness of research data objects based on [metrics](https://doi.org/10.5281/zenodo.3775793) developed by the [FAIRsFAIR](https://www.fairsfair.eu/) project. -The service will be applied to demostrate the evaluation of objects in repositories selected for in-depth collaboration with the project. +F-UJI is a web service to programmatically assess FAIRness of research data objects based on [metrics](https://doi.org/10.5281/zenodo.3775793) developed by the [FAIRsFAIR](https://www.fairsfair.eu/) project. +The service will be applied to demonstrate the evaluation of objects in repositories selected for in-depth collaboration with the project. The '__F__' stands for FAIR (of course) and '__UJI__' means 'Test' in Malay. So __F-UJI__ is a FAIR testing tool. @@ -19,18 +19,18 @@ Devaraju, A. and Huber, R. (2021). An automated solution for measuring the progr ### Clients and User Interface -A web demo using F-UJI is available at https://www.f-uji.net +A web demo using F-UJI is available at . -An R client package that was generated from the F-UJI OpenAPI definition is available from https://github.com/NFDI4Chem/rfuji. +An R client package that was generated from the F-UJI OpenAPI definition is available from . -An open source web client for F-UJI is available at https://github.com/MaastrichtU-IDS/fairificator. +An open source web client for F-UJI is available at . ## Assessment Scope, Constraint and Limitation The service is **in development** and its assessment depends on several factors. - In the FAIR ecosystem, FAIR assessment must go beyond the object itself. FAIR enabling services and repositories are vital to ensure that research data objects remain FAIR over time. Importantly, machine-readable services (e.g., registries) and documents (e.g., policies) are required to enable automated tests. - In addition to repository and services requirements, automated testing depends on clear machine assessable criteria. Some aspects (rich, plurality, accurate, relevant) specified in FAIR principles still require human mediation and interpretation. -- The tests must focus on generally applicable data/metadata characteristics until domain/community-driven criteria have been agreed (e.g., appropriate schemas and required elements for usage/access control, etc.). For example, for some of the metrics (i.e., on I and R principles), the automated tests we proposed only inspect the ‘surface’ of criteria to be evaluated. Therefore, tests are designed in consideration of generic cross-domain metadata standards such as dublin core, dcat, datacite, schema.org, etc. -- FAIR assessment is performed based on aggregated metadata; this includes metadata embedded in the data (landing) page, metadata retrieved from a PID provider (e.g., Datacite content negotiation) and other services (e.g., re3data). +- The tests must focus on generally applicable data/metadata characteristics until domain/community-driven criteria have been agreed (e.g., appropriate schemas and required elements for usage/access control, etc.). For example, for some metrics (i.e., on I and R principles), the automated tests we proposed only inspect the ‘surface’ of criteria to be evaluated. Therefore, tests are designed in consideration of generic cross-domain metadata standards such as Dublin Core, DCAT, DataCite, schema.org, etc. +- FAIR assessment is performed based on aggregated metadata; this includes metadata embedded in the data (landing) page, metadata retrieved from a PID provider (e.g., DataCite content negotiation) and other services (e.g., re3data). ![alt text](https://github.com/pangaea-data-publisher/fuji/blob/master/fuji_server/static/main.png?raw=true) @@ -38,9 +38,9 @@ The service is **in development** and its assessment depends on several factors. [Python](https://www.python.org/downloads/) `3.11+` ### Google Dataset Search -* Download the latest Dataset Search corpus file from: https://www.kaggle.com/googleai/dataset-search-metadata-for-datasets -* Open file fuji_server/helper/create_google_cache_db.py and set variable 'google_file_location' according to the file location of the corpus file -* Run create_google_cache_db.py which creates a SQLite database in the data directory. From root directory run `python3 -m fuji_server.helper.create_google_cache_db`. +* Download the latest Dataset Search corpus file from: +* Open file `fuji_server/helper/create_google_cache_db.py` and set variable 'google_file_location' according to the file location of the corpus file +* Run `create_google_cache_db.py` which creates a SQLite database in the data directory. From root directory run `python3 -m fuji_server.helper.create_google_cache_db`. The service was generated by the [swagger-codegen](https://github.com/swagger-api/swagger-codegen) project. By using the [OpenAPI-Spec](https://github.com/swagger-api/swagger-core/wiki) from a remote server, you can easily generate a server stub. @@ -49,36 +49,31 @@ The service uses the [Connexion](https://github.com/spec-first/connexion) librar ## Usage Before running the service, please set user details in the configuration file, see config/users.py. -To install F-UJI, you may execute the following python-based or docker-based installation commands from the root directory: +To install F-UJI, you may execute the following Python-based or docker-based installation commands from the root directory: -### Python module-based installation: +### Python module-based installation -From the fuji source folder run +From the fuji source folder run: ```bash -pip install . -``` -The F-UJI server can now be started with. +python -m pip install . ``` +The F-UJI server can now be started with: +```bash python -m fuji_server -c fuji_server/config/server.ini ``` -### Docker-based installation: +### Docker-based installation ```bash docker run -d -p 1071:1071 ghcr.io/pangaea-data-publisher/fuji ``` -To access the OpenAPI user interface, open the url below on the browser: - -``` -http://localhost:1071/fuji/api/v1/ui/ -``` +To access the OpenAPI user interface, open the URL below in the browser: + Your OpenAPI definition lives here: -``` -http://localhost:1071/fuji/api/v1/openapi.json -``` + You can provide a different server config file this way: @@ -95,12 +90,12 @@ docker run -d -p 1071:1071 ### Notes -To avoid tika startup warning message, set environment variable TIKA_LOG_PATH. For more information, see [https://github.com/chrismattmann/tika-python](https://github.com/chrismattmann/tika-python) +To avoid Tika startup warning message, set environment variable `TIKA_LOG_PATH`. For more information, see [https://github.com/chrismattmann/tika-python](https://github.com/chrismattmann/tika-python) -If you receive the exception 'urllib2.URLError: