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FAIR principles for research data

In recent years, the concept of FAIR data has intensified. This is due in part because the EU requires that research data within H2020 comply with FAIR principles.

FAIR stands for Findable, Accessible, Interoperable and Reusable. Among other things, this means that data is to be understandable for both humans and machines, today and in the future.

You will find more about the underlying principles of FAIR in this compilation.

In other words, good data management and increased quality in scientific production and increased opportunities for reuse. It is important to point out that research data that complies with these principles to a large extent, does not necessarily have to be open access.

On the other hand, open access to available research data does not automatically comply with FAIR. For instance, a principal investigator may request that ethical review decisions be submitted. In contrast, documentation may be missing or stored in a long-term data format at the next phase. So, research data can, to varying extent, be FAIR.

More information about FAIR can be found at GO FAIR. More information about the principles can be found under FAIR Principles. These principles have been developed over several years but originate in the article “FAIR Guiding Principles for scientific data management and stewardship” in Scientific Data (2016). The Swedish National Data Service has also compiled a list of the four main principles of FAIR.