The newly published article on transparent evaluations of FAIRness that is increasingly required by a wide range of stakeholders, from scientists to publishers, funding agencies and policy makers, “Evaluating FAIR maturity through a scalable, automated, community-governed framework”, shed a light on a scalable, automatable framework to evaluate digital resources that encompasses measurable indicators, open source tools, and participation guidelines, which come together to accommodate domain relevant community-defined FAIR assessments. Technical and social considerations of FAIR assessments and how it translates to a community-driven infrastructure are taken into consideration to incrementally and realistically improve the FAIRness of the resources.
Evaluating FAIR Maturity Through a Scalable, Automated, Community-Governed Framework, MD Wilkinson, Michel Dumontier, Susanna-Assunta Sansone, Luiz Olavo Bonino da Silva Santos, Mario Prieto, Dominique Batista, Peter McQuilton, Tobias Kuhn, Philippe Rocca-Serra, Mercè Crosas, Erik Schultes, bioRxiv 649202; doi: https://doi.org/10.1101/649202
M.D. Wilkinson work is supported by the funding from the European Union’s Horizon 2020 research and innovation programme under the EJP RD COFUND-EJP N° 825575