FAIR Data Maturity Model WG Case Statement

Publié le 24 septembre 2018, par Thérèse Hameau

La proposition de Groupe de Travail "FAIR data maturity model : Core criteria to assess the implementation level of the FAIR data principles" est ouverte pour commentaires de la communauté RDA.

« 1.WG charter

1. Context


Findability, Accessibility, Interoperability and Reusability – the FAIR principles – were first introduced in 2014 and intend to define a minimal set of community-agreed guiding principles and practices that allow both machines and humans to find, access, interoperate and re-use research data. The FAIR principles define characteristics that contemporary research data resources, vocabularies and infrastructures should exhibit to assist discovery and reuse by third-parties and they can be further refined into a range of facets that have the potential to : a) improve scientific research, b) contribute to growth and accelerate innovation in a global digital economy, c) increase the reproducibility of research and d) better inform citizens and society about the results and value of research (through thorough and comprehensible description of the data sets).


2. Problem

Due to the lack of a common set of core assessment criteria for FAIRness, researchers and organisations cannot evaluate the readiness and implementation level of their datasets vis-à-vis the FAIR data principles in a coherent way. The majority of the available FAIR assessment frameworks : i) produce results which cannot be combined or compared and ii) do not allow a benchmark based on the comparison amongst peers. In addition, research performing organisations and data infrastructures cannot develop or follow a minimum set of shared guidelines to climb up the ladder of FAIR because of the increased heterogeneity of the offered FAIR metrics tools.


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 [...]

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