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Research data management

Research data management (RDM) refers to the administration of data throughout a research project, including requirements on preservation and sharing after the project ends.

What is FAIR Data?

FAIR data are data which meet the principles of findability, accessibility, interoperability, and reusability (Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; et al. (15 March 2016). "The FAIR Guiding Principles for scientific data management and stewardship". Scientific Data. 3: 160018. doi:10.1038/sdata.2016.18).

A March 2016 publication by a consortium of scientists and organizations specified the "FAIR Guiding Principles for scientific data management and stewardship" in Scientific Data, using FAIR as an acronym and making the concept easier to discuss.



  • Retrievable through standard protocol
  • Authentication and authorisation procedure, where necessary
  • Metadata are accessible, even when the data are no longer available

Commonly-use formats, schemas, and ontologies


  • Richly described, with detailed provenance
  • Released with a clear and accessible data usage licence
  • Domain relevant community standards

The General Data Protection Regulation (GDPR) is a key piece of legislation which underpins FAIR Data. GDPR compliance should be built into your research planning and should be monitored, updated, and improved on a regular basis.

Find out more about GDPR on the Cranfield page here.

When writing a data management plan, the Horizon 2020 (H2020) template asks about making your data FAIR. Please refer to the Guidelines on Data Management in Horizon 2020 for more information.