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DANS is an institute of KNAW and NWO
Data Archiving and Networked Services
FAIR enough?
FAIR Assessment for Researchers and Repositories
Eliane Fankhauser (DANS)
EOSC Stakeholder Forum
Vienna, 22 November, 2018
FAIR assessment tools
• Checklist “How FAIR are your data?
– “A Checklist produced for use at the EUDAT summer school to
discuss how FAIR the participant's research data were…”
• FAIR self-assessment tool
– Provided by ANDS / Nectar / RDS
– ”… designed predominantly for data librarians and IT staff…”
• FAIRdat tool
– “Using this tool you will be able to score the 'FAIRness' of a
dataset.”
FAIRdat tool
• Established at DANS (2016 – 2017)
• Check FAIRness of any datasets deposited or re-
used in a repository
• Aim (2017): implementation in DANS EASY and
DataverseNL
• Review result: FAIRness on a scale of 1 to 5 stars
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slide. For all other information please use the slide with
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Only use this slide to present a screenshot of an application.
As no style is applied, the screenshot can take up the whole
slide. For all other information please use the slide with
preset style!
Only use this slide to present a screenshot of an application.
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slide. For all other information please use the slide with
preset style!
Only use this slide to present a screenshot of an application.
As no style is applied, the screenshot can take up the whole
slide. For all other information please use the slide with
preset style!
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As no style is applied, the screenshot can take up the whole
slide. For all other information please use the slide with
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• Current version is pilot version
• I = R
– Questions about F, A and R
• Feedback after testing
– Questions are unclear at times (causing misunderstandings)
– Better to formulate questions per letter
– Lack of overview
– Problem of FAIR on the level of the repository and the level of
datasets
FAIR checklist for researchers
• Short and concise checklist for researchers who
are planning to deposit their data
• Covers different levels of FAIRness (repository,
metadata, dataset, files)
Overview content
11 questions in total
Data repository: 1 question
Findablility: 3 questions
Accessability: 1 question
Interoperability: 2 questions
Reusability: 3 questions
Addidional question: 1 question about openness of
dataset(s)
Checklist demonstration
Checklist “FAIR enough?”
Summary
• Questions formulated as simple as possible
• No direct ”translation” of FAIR principles
• Short explanations of terms and concepts
• Reference to trustworthy repositories and CTS
• Overall score at the end
• “Recommendations” for questions answered with
no
Next steps
• Ask for feedback from a broad range of
researchers
• Integrate checklist in the environment of DANS
EASY as an additional website
FAIR checklist factsheet
FAIR and repositories
• Paper about FAIR and the CoreTrustSeal
requirements by Mustapha Mokrane
– Comparison between FAIR principles and CTS requirements
– Mapping of FAIR principles and CTS requirements
– Shows which data-level elements of FAIR are not covered and
where extensions are needed
DANS is an institute of KNAW and NWO
Data Archiving and Networked Services
Thank you for your
attention!
Eliane Fankhauser
eliane.fankhauser@dans.knaw.nl
www.dans.knaw.nl
Twitter: @DANSKNAW

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FAIR Assessment for Repositories and Researchers

  • 1. DANS is an institute of KNAW and NWO Data Archiving and Networked Services FAIR enough? FAIR Assessment for Researchers and Repositories Eliane Fankhauser (DANS) EOSC Stakeholder Forum Vienna, 22 November, 2018
  • 2. FAIR assessment tools • Checklist “How FAIR are your data? – “A Checklist produced for use at the EUDAT summer school to discuss how FAIR the participant's research data were…” • FAIR self-assessment tool – Provided by ANDS / Nectar / RDS – ”… designed predominantly for data librarians and IT staff…” • FAIRdat tool – “Using this tool you will be able to score the 'FAIRness' of a dataset.”
  • 3. FAIRdat tool • Established at DANS (2016 – 2017) • Check FAIRness of any datasets deposited or re- used in a repository • Aim (2017): implementation in DANS EASY and DataverseNL • Review result: FAIRness on a scale of 1 to 5 stars
  • 4. Only use this slide to present a screenshot of an application. As no style is applied, the screenshot can take up the whole slide. For all other information please use the slide with preset style!
  • 5. Only use this slide to present a screenshot of an application. As no style is applied, the screenshot can take up the whole slide. For all other information please use the slide with preset style!
  • 6. Only use this slide to present a screenshot of an application. As no style is applied, the screenshot can take up the whole slide. For all other information please use the slide with preset style!
  • 7. Only use this slide to present a screenshot of an application. As no style is applied, the screenshot can take up the whole slide. For all other information please use the slide with preset style!
  • 8. Only use this slide to present a screenshot of an application. As no style is applied, the screenshot can take up the whole slide. For all other information please use the slide with preset style!
  • 9. Only use this slide to present a screenshot of an application. As no style is applied, the screenshot can take up the whole slide. For all other information please use the slide with preset style!
  • 10. Only use this slide to present a screenshot of an application. As no style is applied, the screenshot can take up the whole slide. For all other information please use the slide with preset style!
  • 11. • Current version is pilot version • I = R – Questions about F, A and R • Feedback after testing – Questions are unclear at times (causing misunderstandings) – Better to formulate questions per letter – Lack of overview – Problem of FAIR on the level of the repository and the level of datasets
  • 12. FAIR checklist for researchers • Short and concise checklist for researchers who are planning to deposit their data • Covers different levels of FAIRness (repository, metadata, dataset, files)
  • 13. Overview content 11 questions in total Data repository: 1 question Findablility: 3 questions Accessability: 1 question Interoperability: 2 questions Reusability: 3 questions Addidional question: 1 question about openness of dataset(s)
  • 15. Summary • Questions formulated as simple as possible • No direct ”translation” of FAIR principles • Short explanations of terms and concepts • Reference to trustworthy repositories and CTS • Overall score at the end • “Recommendations” for questions answered with no
  • 16. Next steps • Ask for feedback from a broad range of researchers • Integrate checklist in the environment of DANS EASY as an additional website
  • 18. FAIR and repositories • Paper about FAIR and the CoreTrustSeal requirements by Mustapha Mokrane – Comparison between FAIR principles and CTS requirements – Mapping of FAIR principles and CTS requirements – Shows which data-level elements of FAIR are not covered and where extensions are needed
  • 19. DANS is an institute of KNAW and NWO Data Archiving and Networked Services Thank you for your attention! Eliane Fankhauser eliane.fankhauser@dans.knaw.nl www.dans.knaw.nl Twitter: @DANSKNAW