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RDMbites | FAIRification: a case study

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Relevant links:
1. Corona Accelerated R&D in Europe (CARE): https://www.imi.europa.eu/projects-results/project-factsheets/care
2. FAIR Data Maturity Model: specification and guidelines: https://zenodo.org/records/3909563
3. Dataset pre-assessment results: https://fairplus.github.io/fairification-results/2021-07-20-CARE-pre-assessment/
4. Dataset post-assessment results: https://fairplus.github.io/fairification-results/2021-10-01-CARE-post-assessment/
5. The FAIRified dataset: https://www.ebi.ac.uk/chembl/document_report_card/CHEMBL4651402/
6. The success story on IMI CARE case study: https://fairplus-project.eu/case-studies/imi-care
7. The FAIR Wizard: https://www.ebi.ac.uk/ait/fair-wizard/

The RDMbites are funded by the ELIXIR-UK: FAIR Data Stewardship training UKRI award (MR/V038966/1)

00:00 Learning objectives
00:33 Project overview
01:15 FAIRification goal
01:41 Pre-assessment results and interpretation
02:26 Tailored FAIRification Process
04:20 Post-assessment results
05:09 Analysis of Improvements
05:57 Impact
06:56 Acknowledgments

Licence: Creative Commons Attribution 4.0 International

Contact: contact@elixiruknode.org

Keywords: data management, RDM

Resource type: Video Lecture

Learning objectives:

Exemplar FAIRification – IMI CARE case study

Contributors: Lijing Lin, Nick Juty

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