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FAIR Data in Trustworthy Repositories: Everybody wants to play FAIR, but how do we put the principles into practice?

Presenter 1
Ingrid Dillo
Data Archiving and Networked Services (DANS)
Presenter 2
Peter Doorn
Data Archiving and Networked Services (DANS)

There is a growing demand for quality criteria for research datasets. We will argue that the Data Seal of Approval and FAIR principles get as close as possible to giving quality criteria for research data. They do not do this by trying to make value judgements about the content of datasets, but rather by qualifying the fitness for data reuse in an impartial and measurable way. By bringing the ideas of the DSA and FAIR together, we will be able to offer an operationalization that can be implemented in any Trustworthy Digital Repository. 

In 2014 the FAIR Principles were formulated. The well-chosen FAIR acronym is attractive: it almost automatically gets stuck in your mind once you have heard it. In a relatively short term, the FAIR data principles have been adopted by many stakeholders, including research funders.

The FAIR principles are remarkably similar to the underlying principles of DSA (2005): the data can be found on the Internet, are accessible, in a usable format, reliable and are identified in a unique and persistent. The DSA presents quality criteria for repositories, whereas the FAIR principles target individual datasets. The two sets of principles will be discussed and compared and a tangible operationalization will be presented.

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