FAIR Data Maturity Model WG Case Statement

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3. Outcomes

The Working Group `FAIR data maturity model: core criteria to assess the implementation level of the FAIR data principles` will bring 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. The Working Group will develop 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 from the following perspectives:
– Data findability, i.e. how well it describes the data it produces or manages with rich metadata, assigns to data/metadata a globally unique persistent identifier and registers or indexes them in a searchable resource;
– Data accessibility, i.e. how well it allows the retrieval of its data/metadata by their identifier using a standardized communications protocol that is open, free and universally implementable;
– Data interoperability, i.e. how well it ensures that the precise format and meaning of exchanged and shared data/metadata is preserved and understood;
– Data reusability, i.e. how well it releases data/metadata with a clear and accessible data usage license, associated with detailed provenance and follows practices that promote the reuse and share of data, unless certain privacy or confidentiality restrictions apply.

In addition, the Working Group will design:

– A self-assessment toolset that enables researchers and organisations to evaluate and improve the readiness and implementation level of their datasets vis-à-vis the FAIR data principles.
– A lightweight version of the FAIR Data Maturity Model (aka FAIR data checklist), aiming to raise awareness on the main aspects related with the FAIR principles.

The outcomes of the Working Group will be possible to be applied not only to data in the conventional sense but also to data-related algorithms, tools, workflows, protocols and other data-related services produced or managed by the assessed entity.

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