status: Recognised & Endorsed
Chair (s): Edit Herczog, Keith Russell, Shelley Stall, Sarah Jones
Group Email: [group_email]
Secretariat Liaison: enquiries@rd-alliance.org
FAIR Data Maturity Model: core criteria to assess the implementation level of the FAIR data principles
Webinar - The RDA FAIR Data Maturity Model WG: Aligning International Initiatives for Promoting and Assessing FAIR Data - 19/11/2020
Webinar - Connecting Data, Institutions and People: FAIR Digital Objects, RDA outputs and the design of the DiSSCo Research Infrastructure - 18 March 2021
The RDA FAIR Data Maturity Model Working Group develops as an RDA Recommendation a common set of core assessment criteria for FAIRness and a generic and expandable self-assessment model for measuring the maturity level of a dataset. The aim is not to develop yet another FAIR assessment approach but to build on existing initiatives, looking at common elements and allowing the group to identify core elements for the evaluation of FAIRness. That will increase the coherence and interoperability of existing or emerging FAIR assessment frameworks and it will ensure the combination and compatibility of their results in a meaningful way.
The WG brings together stakeholders from different scientific and research disciplines, the industry and public sector, who are active and/or interested in the FAIR data principles and in particular in assessment criteria and methodologies for evaluating their real-life uptake and implementation level.
Outputs
Member survey on bridging the gap between funders and communities – perspectives on benefits and challenges of FAIR assessments V2.0
This report provides a consolidated view of the answers collected during a survey conducted in October 2020. This survey was conducted amongst members of the RDA FAIR Data Maturity Model Working Group and aimed at investigating the differences of perspectives on benefits and challenges of the FAIR assessments between members representing funders and research communities.
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FAIR Data Maturity Model: specification and guidelines
This document describes a maturity model for FAIR assessment with assessment indicators, priorities and evaluation methods. This is useful for the normalisation of assessment approaches to enable comparison of their results.
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FAIR Data Maturity Model: specification and guidelines - draft
Findability, Accessibility, Interoperability and Reusability – the FAIR principles – intend to define a minimal set of related but independent and separable guiding principles and practices that enable both machines and humans to find, access, interoperate and re-use research data and metadata. The FAIR principles have to be considered as inspiring concepts but not strict rules. Unfortunately, they often lead to diverse interpretations and ambiguity.
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Results of an Analysis of Existing FAIR Assessment Tools
This document is a first output of the FAIR Data Maturity Model WG. This resulted in five slide decks, combined in this pdf document, that make up this preliminary analysis.
The document was updated after the community review period, and the current version v3 is attached to this page. The previous version v0.02, which underwent the community review, is also available.
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