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Research Data: FAIR Data

 

Research data that is findable, accessible, interoperable and reusable (FAIR) enriches the research landscape and enables data-driven research. The FAIR principles are now widely acknowledged as best guidelines for data management.  

FAIR Data

Findable
It should be possible for others to discover your data. Rich metadata should be available online in a searchable resource, and the data should be assigned a persistent identifier.

  • A persistent identifier is assigned to your data
  • There are rich metadata, describing your data
  • The metadata are online in a searchable resource e.g. a catalogue or data repository
  • The metadata record specifies the persistent identifier

Accessible
It should be possible for humans and machines to gain access to your data, under specific conditions or restrictions where appropriate. FAIR does not mean that data need to be open! There should be metadata, even if the data aren’t accessible.

  • Following the persistent ID will take you to the data or associated metadata
  • The protocol by which data can be retrieved follows recognised standards e.g. http
  • The access procedure includes authentication and authorisation steps, if necessary
  • Metadata are accessible, wherever possible, even if the data aren’t

Interoperable
Data and metadata should conform to recognised formats and standards to allow them to be combined and exchanged.

  • Data is provided in commonly understood and preferably open formats
  • The metadata provided follows relevant standards
  • Controlled vocabularies, keywords, thesauri or ontologies are used where possible
  • Qualified references and links are provided to other related data

Reusable
Lots of documentation is needed to support data interpretation and reuse. The data should conform to community norms and be clearly licensed so others know what kinds of reuse are permitted.

  • The data are accurate and well described with many relevant attributes
  • The data have a clear and accessible data usage license
  • It is clear how, why and by whom the data have been created and processed
  • The data and metadata meet relevant domain standards

 

Taken from the ‘How FAIR are your data?’ checklist, CC-BY by Sarah Jones & Marjan Grootveld, EUDAT. Image CC-BY-SA by SangyaPundir

Video: What could possibly go wrong?

Data not managed according to FAIR principles can cause many headaches. Learn about the troubles Dr. Judy Benign is facing in her quest to reuse some data in this short and entertaining video.

Towards FAIR and Open Data

FAIR data does not necessarily need to be Open Data. Access can be restricted for example for ethical, legal or commercial reasons. The most valuable contribution to an open research landscape is however data that is both managed according to FAIR principles and made available without restrictions. (graphic by Sarah Jones)