FAIR Research Data Principles are currently aimed at and being applied by different communities, research disciplines, and research stakeholders. But how can we really determine how much FAIRness is intended or needed to make research artefacts (including data) Findable, Accessible, Interoperable, and Reusable?
This recent Task Force Report created by the EOSC Task Force on FAIR Metrics and Data Quality sheds light on this complex issue.
The Task Force discovered that FAIR is evolving in both expected and unexpected ways. The report explains how the lack of a clear standard for and definition of “FAIR behaviours” has encouraged stakeholders to define the existing approaches as being FAIR-compliant rather than truly FAIR.
Overall conclusions?
In addition, the report identifies three high-level stakeholder categories: FAIR decision- and policymakers, FAIR custodians, and FAIR practitioners. It also provides examples outlining specific stakeholders’ (hypothetical but anticipated) needs.