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OSFair2017 Training Outcomes | FAIR metrics - Starring your data sets

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Workshop abstract:
Do you want to join our effort to put the FAIR data principles into practice? Come and explore the assessment tool that DANS, Data Archiving and Networked Services in the Netherlands, is developing for data repositories.
The aim of our work is to implement the FAIR principles into a data assessment tool so that every dataset which is deposited or reused from any digital repository can be assessed in terms of a score on the principles Findable, Accessible, Interoperable, and Reusable, using a ‘FAIRness’ scale from 1 to 5 stars. In this interactive session participants can explore the pilot version of FAIRdat: the FAIR data assessment tool. The organisers would like to inform you about the project, and look forward to all feedback to improve the tool, or to improve the metrics that are used.

Peter Doorn, Data Archiving and Networked Services (DANS)
Marjan Grootveld, Data Archiving and Networked Services (DANS)
Elly Dijk, Data Archiving and Networked Services (DANS)


Publié dans : Sciences
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OSFair2017 Training Outcomes | FAIR metrics - Starring your data sets

  1. 1. www.dans.knaw.nl DANS is an institute of KNAW and NWO @pkdoorn @dansknaw FAIR metrics - Starring your Data Sets, Athens, 8 Sept 2017 A Lightweight FAIR Data Assessment Tool Peter Doorn, Elly Dijk & Marjan Grootveld, DANS Thanks to Emily Thomas and Eleftheria Tsoupra
  2. 2. The main actions to take now • Continue the FAIRdat approach to translate the FAIR data principles into practical metrics (operationisation) • Invite more people and organisations to validate the FAIRdat prototype. • Inform about this pilot project on the DANS website  • Make the FAIRdat tool (first as beta-version) available on an independent website
  3. 3. The main recommendations • Define clear target groups for assessing the FAIRness of datasets: • Data producers = data depositing researchers (self- assessment) • Data professionals, e.g. in data repositories • Data consumers: they can assess after they have re-used • Others? Journals? • Reconsider if the Reusable metric follows from F & A & I. • We need your feedback and recommendations for this! • Consider using scales instead of Yes/No questions. • Encourage people to assess how FAIR existing data are • In addition to making new data FAIR
  4. 4. Thank you for listening! peter.doorn@dans.knaw.nl www.dans.knaw.nl http://www.dtls.nl/go-fair/ https://eudat.eu/events/webinar/fair-data-in-trustworthy-data-repositories- webinar Thanks to Ingrid Dillo and Emily Thomas for their contributions