Contents for analysing data: Difference between revisions
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* [https://fairsharing.github.io/FAIR-Evaluator-FrontEnd/#!/ FAIR Evaluation Services] | * [https://fairsharing.github.io/FAIR-Evaluator-FrontEnd/#!/ FAIR Evaluation Services] | ||
* [https://www.fairsfair.eu/f-uji-automated-fair-data-assessment-tool F-UJI Automated FAIR Data Assessment Tool] | |||
* [https://fair-checker.france-bioinformatique.fr/ FAIR-Checker] | |||
Latest revision as of 15:11, 17 November 2022
A proper understanding of the data is essential for carrying out any FAIRification activity. If the data are own data or coming from an in-house activity, such an understanding may come easily. But if the data are provided by a third party, a detailed analysis might be necessary. This step analyses the data to support the FAIRification step. Issues to be considered are:
- How are the data organized? Do the data meet the intended formatting? Are data missing?
- Are some FAIR features already existing in the data such as persistent identifiers? If the data are extensive, running a (semi-) automatic FAIR assessment tool is helpful.
Here is a list of (semi-) automatic tools: