Community-driven governance of FAIRness assessment: an open issue, an open discussion.

Autor:	Wilkinson MD; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Centro de Biotecnología y Genómica de Plantas. Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria-CSIC (INIA-CSIC), Madrid, Spain., Sansone SA; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; Department of Engineering Science, Oxford e-Research Centre, The University of Oxford, Oxford, UK., Méndez E; Library and Information Science Department, Universidad Carlos III de Madrid, Madrid, Spain., David R; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; European Research Infrastructure on Highly Pathogenic Agents (ERINHA AISBL), Brussels, Belgium., Dennis R; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; Novo Nordisk Foundation Center for Stem Cell Medicine - reNEW, University of Copenhagen, Copenhagen, Denmark., Hecker D; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; Research Data Management, German Aerospace Center (DLR), Cologne, Germany., Kleemola M; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; Finnish Social Science Data Archive and CESSDA ERIC, Tampere University, Tampere, Finland., Lacagnina C; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; Barcelona Supercomputing Center, Barcelona, Spain., Nikiforova A; EOSC Task Force on FAIR Metrics and Data Quality, EOSC, Brussels, Belgium.; Institute of Computer Science, The University of Tartu, Tartu, Estonia., Castro LJ; Semantic Technologies team, ZB MED Information Centre for Life Sciences, Cologne, Germany.
Jazyk:	angličtina
Zdroj:	Open research Europe [Open Res Eur] 2023 Sep 06; Vol. 2, pp. 146. Date of Electronic Publication: 2023 Sep 06 (Print Publication: 2022).
DOI:	10.12688/openreseurope.15364.2
Abstrakt:	Although FAIR Research Data Principles are targeted at and implemented by different communities, research disciplines, and research stakeholders (data stewards, curators, etc.), there is no conclusive way to determine the level of FAIRness intended or required to make research artefacts (including, but not limited to, research data) Findable, Accessible, Interoperable, and Reusable. The FAIR Principles cover all types of digital objects, metadata, and infrastructures. However, they focus their narrative on data features that support their reusability. FAIR defines principles, not standards, and therefore they do not propose a mechanism to achieve the behaviours they describe in an attempt to be technology/implementation neutral. Various FAIR assessment metrics and tools have been designed to measure FAIRness. Unfortunately, the same digital objects assessed by different tools often exhibit widely different outcomes because of these independent interpretations of FAIR. This results in confusion among the publishers, the funders, and the users of digital research objects. Moreover, in the absence of a standard and transparent definition of what constitutes FAIR behaviours, there is a temptation to define existing approaches as being FAIR-compliant rather than having FAIR define the expected behaviours. This whitepaper identifies three high-level stakeholder categories -FAIR decision and policymakers, FAIR custodians, and FAIR practitioners - and provides examples outlining specific stakeholders' (hypothetical but anticipated) needs. It also examines possible models for governance based on the existing peer efforts, standardisation bodies, and other ways to acknowledge specifications and potential benefits. This whitepaper can serve as a starting point to foster an open discussion around FAIRness governance and the mechanism(s) that could be used to implement it, to be trusted, broadly representative, appropriately scoped, and sustainable. We invite engagement in this conversation in an open Google Group fair-assessment-governance@googlegroups.com. Competing Interests: Competing interests: MDW and SAS are authors of the FAIR Principles. MDW is co-founder of FAIR Data Systems, S.L., Spain - a small enterprise consulting around FAIRness and has produced commercial FAIR assessment tools. LJC is co-author of the FAIR for Research Software principles. (Copyright: © 2023 Wilkinson MD et al.)
Databáze:	MEDLINE
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