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Assessment of Data Fitness for Use

This project aims to develop criteria and a fitness for use label to assess the quality of research data. The pilot implementation will involve data depositors, repositories, and users.

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Assessment of Data Fitness for Use

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  1. WDS/RDA Assessment of Data Fitness for UseClaire Austin, Helena Cousijn, Michael Diepenbroek, Jon Petters

  2. Deliverables Data Fitness group • Descriptions and definitions of data fitness criteria • Development of a fitness for use label based on defined criteria • Piloting the implementation of a fitness for use label

  3. Definitions Draft definitions available here: https://docs.google.com/spreadsheets/d/1a06BM0pZJ3MxuUXbdz9EuLoq4vYf1GmVIenQ6Mp0chs/edit E.g. Data quality is defined by internal characteristics such as completeness, logical consistency, positional and thematic accuracy, temporal quality, etc. RELATED TERM: data fitness for purpose In collaboration with: http://dictionary.casrai.org/Category:Research_Data_Domain Next steps: subgroup will write paper outlining relevant terminology (Claire.Austin@canada.za)

  4. Fitness criteria Mapping of criteria (https://docs.google.com/spreadsheets/d/1NL8EFbxspvt1eT6ZBVxsYYo1SRAtR4lCCiaY2bQdQCs/) • FAIR • ESIP quality cluster • GEO quality criteria 3 perspectives • Data depositors • Data repositories • Data users Checklist/questionnaire for depositors and repositories > ‘label’ for users

  5. Assessing fitness FAIR assessment tool

  6. Assessing fitness FAIR assessment tool pilot • DANS • CCDC • DRYAD • MendeleyData • Virginia Tech Results @ 11am, Mansfield 5! F A I R 2 User Reviews 1 Archivist Assessment 24 Downloads

  7. Questions • Could datasets become part of the CoreTrustSeal? • Would assessing Data Fitness become dependent on repository certification? • Do we need to go beyond FAIR to assess Data Fitness?

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