Data citation

What is data citation?

With many researchers now sharing and reusing data, there is a growing need to cite data as a scholarly output in the same way that traditional print outputs such as books, journal articles and conference papers are acknowledged - by including a bibliographic reference to acknowledge the original data creator/s.

Data citation can help by:

  • enabling easy reuse and verifiction of data
  • allowing the impact of data to be tracked
  • creating a scholarly structure that recognises and rewards data producers

A culture of data citation could result in:

  • data being recognised as a primary research output
  • data use and reuse that could be tracked and recorded in the same way as print publications
  • data citation information being used for research evaluation and reward

Standards for data citation

Standards for data citation vary across disciplines. Some data repositories and archives provide formats for citing data as part of the metadata record for the dataset.

The DataCite Consortium provides a recommended minimum format for citing data:

Required elements:

  • creator
  • publication year
  • title
  • publisher
  • identifier (persistent e.g. DOI)

Optional elements:

  • version
  • resource type (as appropriate)


DataCite format examples of a data citation:

Creator (PublicationYear): Title. Publisher. Identifier