Community-driven Governance of FAIRness assessment

Relevance

This work is pivotal for the research landscape as it addresses the gap in FAIRness assessment accuracy and reproducibility. It proposes a governance mechanism that will refine FAIRness metrics and tests, ensuring they are aligned with FAIR principles and cognizant of the standards across diverse research communities and disciplines.

Scope

The deliverable aims to define a governance model for FAIRness assessments, focusing on creating understandable and trustworthy standards, and providing evaluation tools for transparent and consistent results. Targeted at stakeholders utilising FAIR metrics, it seeks to align tests with qualitative and quantitative FAIRness indicators.

Main highlights

The whitepaper titled “Community-driven Governance of FAIRness Assessment” presents a compelling argument for the establishment of a cohesive and transparent governance model for the evaluation of FAIR principles in research data. It underscores the critical issue of the varied interpretations and applications of FAIRness across different communities, which has led to inconsistency and confusion. Importantly, the paper clarifies that it does not advocate for governance over the FAIR Principles themselves, which it suggests should remain untouched. Instead, it advocates for a governance structure aimed at harmonising these interpretations to ensure the principles are applied effectively and uniformly.

The document thoroughly discusses the current inadequacies found in FAIRness assessment tools, highlighting their lack of necessary accuracy and reproducibility. It points out the significant benefits a standardised approach would bring to a wide range of stakeholders, including researchers, publishers, and policymakers. By adopting a unified governance mechanism, these stakeholders would be able to rely on FAIRness assessments that are both trustworthy and sustainable, ensuring that these assessments are universally reliable and accepted across diverse research disciplines.

Key recommendations

The document advocates for a FAIRness governance model to ensure that FAIR assessments are objective, transparent, and consistent across various domains and communities.

Key recommendations for such a model include: 1) Compatibility and cohesion of tools and services for evaluating FAIRness, 2) Universal understanding and trust in the FAIRness assessment process by both producers and users of digital research objects, and 3) Adaptability of FAIRness to specific domain needs and a wide range of digital objects, while ensuring transparency, consistency, and trust among all stakeholders​.