The FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments.
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Date
2020Author
Bahim, Christophe
Casorrán-Amilburu, Carlos
Dekkers, Makx
Herczog, Edit
Loozen, Nicolas
Repanas, Konstantinos
Russell, Keith
Stall, Shelley
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In the past years, many methodologies and tools have been developed to assess the FAIRness of research data. These different methodologies and tools have been based on various interpretations of the FAIR principles, which makes comparison of the results of the assessments difficult. The work in the RDA FAIR Data Maturity Model Working Group reported here has delivered a set of indicators with priorities and guidelines that provide a ‘lingua franca’ that can be used to make the results of the assessment using those methodologies and tools comparable. The model can act as a tool that can be used by various stakeholders, including researchers, data stewards, policy makers and funding agencies, to gain insight into the current FAIRness of data as well as into the aspects that can be improved to increase the potential for reuse of research data. Through increased efficiency and effectiveness, it helps research activities to solve societal challenges and to support evidence-based decisions. .....
Journal
Data Science JournalVolume
19Issue
Article 41Page Range
7pp.Document Language
enSustainable Development Goals (SDG)
14.AMaturity Level
TRL 7 System prototyping demonstration in an operational environment (ground or space)Best Practice Type
Manual (incl. handbook, guide, cookbook etc)DOI Original
https://doi.org/10.5334/dsj-2020-041Citation
Bahim, C., Casorrán-Amilburu, C., Dekkers, M., Herczog, E., Loozen, N., Repanas, K., Russell, K. and Stall, S. (2020) The FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments. Data Science Journal, 19: 41. 7pp. DOI: http://doi.org/10.5334/dsj-2020-041Collections
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