Published June 29, 2021 | Version v1
Project deliverable Open

D2.5 FAIRplus FAIR Data Maturity Framework

  • 1. Fraunhofer
  • 2. Imperial College
  • 3. University of Oxford
  • 4. University of Manchester
  • 5. AstraZeneca
  • 6. Bayer
  • 7. EMBL-EBI
  • 8. ELIXIR Hub


FAIRplus seeks to establish ‘FAIRification’ processes that can be used at scale to ensure FAIRness of IMI data. The goal of the FAIRplus Maturity Framework is to help the IMI office, IMI projects, and EFPIA partners analyse and plan their advancement in creation and maintenance of FAIR data. To this end, the work package aims to deliver two maturity models. One is a Data Management Maturity Model which focuses on ensuring that processes in place support the creation of new FAIR datasets, the second is the Dataset Maturity Model which is regarding the FAIRness of existing datasets. These two maturity models fit into the updated FAIRplus FAIRification process; the Dataset Maturity Model supports the data requirements task while the Data Management Maturity Model supports the task to identify FAIRification capabilities and resources.

These models will be aligned with and based on the RDA FAIR indicators. However, before including them, an analysis was done on their suitability for use with human data as well as their overall clarity. This led to the creation of FAIR Assessment Indicators on which the Maturity Models will be built.


D2.5 FAIRplus FAIR Data Maturity Framework.pdf

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FAIRplus – FAIRplus 802750
European Commission