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dc.contributor.authorBahim, Christophe
dc.contributor.authorCasorrán-Amilburu, Carlos
dc.contributor.authorDekkers, Makx
dc.contributor.authorHerczog, Edit
dc.contributor.authorLoozen, Nicolas
dc.contributor.authorRepanas, Konstantinos
dc.contributor.authorRussell, Keith
dc.contributor.authorStall, Shelley
dc.date.accessioned2021-04-06T19:47:01Z
dc.date.available2021-04-06T19:47:01Z
dc.date.issued2020
dc.identifier.citationBahim, 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-2020-041en_US
dc.identifier.urihttp://hdl.handle.net/11329/1534
dc.identifier.urihttp://dx.doi.org/10.25607/OBP-1030
dc.description.abstractIn 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. The Maturity Model is publicly available and the Working Group is encouraging application of the model in practice. Experience with the model will be taken into account in the further development of the model.en_US
dc.language.isoenen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.otherFAIRen_US
dc.subject.otherResearch dataen_US
dc.subject.otherAssessmenten_US
dc.subject.otherDigital objecten_US
dc.subject.otherData managementen_US
dc.subject.otherEvaluationen_US
dc.subject.otherMaturityen_US
dc.titleThe FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments.en_US
dc.typeJournal Contributionen_US
dc.description.refereedRefereeden_US
dc.format.pagerange7pp.en_US
dc.identifier.doihttps://doi.org/10.5334/dsj-2020-041
dc.subject.parameterDisciplineParameter Discipline::Administration and dimensionsen_US
dc.subject.dmProcessesData Management Practices::Data archival/stewardship/curationen_US
dc.bibliographicCitation.titleData Science Journalen_US
dc.bibliographicCitation.volume19en_US
dc.bibliographicCitation.issueArticle 41en_US
dc.description.sdg14.Aen_US
dc.description.maturitylevelTRL 7 System prototyping demonstration in an operational environment (ground or space)en_US
dc.description.bptypeManual (incl. handbook, guide, cookbook etc)en_US
obps.contact.contactnameChristophe Bahim
obps.contact.contactemailchristophe.bahim@pwc.com
obps.resourceurl.publisherhttps://datascience.codata.org/articles/10.5334/dsj-2020-041/en_US


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International