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Research Data Management: Citing Data

This library guide outlines the basics of data management and creating a data management plan.

Reasons for Citing Data

Data requires citations for the same reasons journal articles and other types of publications require citations: to acknowledge the original author/producer and to help other researchers find the resource.

Citing data is important because it:

  • Acknowledges and provides credit to the originator of the data
  • Allows verification of data and results, facilitating their re-use in further research
  • Enables data citation metrics (the impact of data) to be tracked.
Data citation has benefits for researchers as it:
  • Makes data publications more acceptable for CVs and journals
  • Facilitates discovery of grey literature.

The flow chart below from the Australian National Data Service illustrates the benefits of data citation. 

Citing Data

A dataset citation includes all of the same components as any other citation:

  • author,
  • title,
  • year of publication,
  • publisher (for data this is often the archive where it is housed),
  • edition or version, and
  • access information (a URL or other persistent identifier such as a doi or handle).

It is important to cite / reference data correctly and consistently. 

The following provide useful guidelines on how to do this:

Citation Software

Citation software helps you to:

  • import citations from your favorite databases and websites.
  • build and organize bibliographies.
  • format citations for papers.
  • take notes on articles and save them in your collection of citations.
  • save and organize PDFs, screenshots, graphs, images, and other files for your research.

Examples include: