FAIRsFAIR Data Object Assessment Metrics
Creators
- 1. University of Bremen (UniHB)
- 2. Data Archiving and Networked Services (DANS-KNAW)
- 3. Digital Curation Center (DCC)
- 4. Digital Curation Centre (DCC)
Contributors
Others:
- 1. UK Data Archive
- 2. Digital Curation Centre (DCC)
Description
This specification contains 14 metrics proposed by FAIRsFAIR to evaluate FAIRness of research data in Trustworthy Digital Repositories (TDRs). We developed the metrics based on existing work (RDA FAIR Data Maturity Model, FAIRdat and FAIREnough, WDS/RDA Assessment of Data Fitness), and adapted them to accommodate the requirements of two main use cases the project prioritized:
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A TDR will offer a self-assessment tool to educate and raise awareness of researchers on making their data FAIR before depositing the data into the repository.
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A TDR committed to FAIR data provision wants to programmatically evaluate published data for their level of FAIRness over time.
To facilitate both use cases, currently we are developing a manual self-assessment tool and an automated assessment service. These tools will support data FAIRness evaluation based on the metrics proposed. They will be piloted with repositories selected for in-depth collaboration with the project iteratively from 1st May 2020 - 31st August 2021. The metrics should not be regarded as final but rather as first prioritized criteria for piloting data FAIRness assessment in the context of the use cases above.
Files
FAIRsFAIR Data Objects Assessment Metrics_v0.2.pdf
Files
(2.1 MB)
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