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Tool | Description | Work on your side |
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FAIR-Checker provides a web interface to automatically evaluate FAIR metrics. It provides users with hints on how to further improve the FAIRness of the resources. FAIRchecker does over 18000 metrics evaluations per month. | In the ‘Check' page, paste an URL or DOI and click on 'Test all metrics’. The assessment will run automatically and return a score for 12 FAIR sub-principles. If a sub-principle does not reach the highest score, you can view recommendations on how to improve. | |
The FAIR Evaluator provides an online service to test (meta)data resources against the Maturity Indicators in an objective, automated way. For an applied example, see Applying the FAIR principles to data in a hospital: challenges and opportunities in a pandemic. The public version of The FAIR Evaluator has been used to assess >5500 datasets. | A guide on how to use the FAIR Evaluator can be found in the FAIR Cookbook. | |
Using FAIRshake, a variety of biomedical digital resources can be manually and automatically evaluated for their level of FAIRness. They provide a variety of rubrics with test-metrics, which can reused, including those proposed by the FAIR Data Maturity Model. The FAIRshake website currently show the results for 132 projects and offers 65 rubics rubrics for reuse. | The extensive documentation (including YouTube tutorials) can be found here. More information is also available in the FAIR Cookbook. |
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