FAIRsFAIR has taken up the challenge to define systematic measurements of data FAIRness and has used the RDA FAIR Data Maturity Model Specification and Guidelines Recommendation of the FAIR Data Maturity Model Working Group to do so.
Given that a number of groups and communities interested in evaluating FAIRness had proposed their own criteria/measures, leading to the proliferation of sometimes ambivalent or incomplete interpretations, FAIRs FAIR has developed a definitive set of minimum metrics for assessing the FAIRness of research data objects and tools. This is in line with FAIRsFAIR's objective to pilot the assessment of digital objects (e.g., research data) in FAIR-enabling Trustworthy Digital Repositories (TDRs). For that reason through an
The minimum metrics constitute an assessment framework that provides consensus based on existing approaches. To support assessments based on the metrics, FAIRsFAIR is currently implementing a tool set (Fair-Aware - a manual self-assessment tool to be used by researchers, and F-UJI - an automated assessment service for implementation by repositories). The metrics and tools will be iteratively improved through pilot testing with researchers and selected data repositories.
The efforts of the FAIR Data Maturity Model Working Group in consolidating feedback and clarifying the principles into a set of indicators are highly appreciated by FAIRsFAIR, and are a significant step forward in FAIR implementation. Recognising that FAIR assessment depends on the data practices of a variety of communities, FAIRsFAIR has adapted the indicators provided in the RDA FAIR Data Maturity Model Specification and Guidelines Recommendation to suit the data and repository requirements of the project’s use cases. In further exploring and elaborating the applicability of the indicators to potential adopters, FAIRsFAIR feels there is a mutual benefit in making contributions to the RDA WG activities.