Put FAIR principles into practice and enjoy your data! | Agricultural Information Management Standards (AIMS)

"Many might have a question: Everybody wants to play FAIR research, but how do we put the principles into practice?

There is a growing demand for quality criteria for research datasets. A number of approaches and recommendation to tackling this issue are proposed by DSA (Data Seal of Approval for data repositories) and FAIR (Findable, Accessible, Interoperable and Reusable) principles.These two recommendations do not make value judgements about the content of datasets, but rather qualify the fitness for data reuse in an impartial and measurable way.

By bringing the ideas of the DSA and FAIR together - that get as close as possible to giving quality criteria for research data - you will be also able to perform an operationalization of DSA & FAIR principles in any certified Trustworthy Digital Repository."