The RDA FAIR Data Maturity Model (FDMM) Specification and Guidelines were published in June 2020 after extensive consultation with the sector. They provide a set of community agreed indicators and priority levels to assess the FAIRness of a data set. Since 2020 the model has been taken up and considered by a range of initiatives around the globe. The aim of this session is to learn from these adoptions and FAIR assessment more broadly and to share what can be learned from these experiences.
Collaborative session notes: https://docs.google.com/document/d/1FVGtj602cL-zw3MUmEDS2Eti_m2OdK9dZ1w6...
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Introduction to the RDA FDMM working group and its achievements (10 mins)
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Perspectives on adoption and implementation of the FAIR Data Maturity Model
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EOSC FAIR metrics and Data Quality Task Force (Carlo Lacagnina, co-chair) TBC (15 mins)
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Interactive session on awareness and adoption of the FAIR Data Maturity Model (15mins)
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How other regions and especially ASEAN region can benefit from FDMM
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Discussion on lessons learned from adoption and implementation of the FAIR Data Maturity Model (30 mins)
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How we can better monitor the progress
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Conclusions and wrap up (5 mins)
Researchers, data service owners, funders and infrastructures 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.
We are interested to meet the newcomers and those are starting their FAIR journey, but also those that are implementing methods around the globe.
The RDA FAIR Data Maturity Working Group was established at the end of 2018 with the objective to 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 completed 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 group has over 250 members representing a wide range of disciplines and regions around the world. The Working Group is now in maintenance mode investigating the implications of the model and FAIR assessment.
Recognised and endorsed in 2018, published the FAIR Data Maturity Model in 2020 and now in maintenance mode.
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Group page: https://www.rd-alliance.org/groups/fair-data-maturity-model-wg
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Some adoption stories of the FAIR Data Maturity Model: https://www.rd-alliance.org/group/fair-data-maturity-model-wg/wiki/adoption-stories-fdmm
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The FAIR Data Maturity Model: https://zenodo.org/record/3909563#.YhhMw-hBy71
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