Why and when to cite

We believe that you should cite data in just the same way that you can cite other sources of information, such as articles and books. Data citation can help by:

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

Advice on citation

The How to Cite Data page by The Michigan State University Libraries provides helpful guidelines for multiple citation styles and advises that 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).

Guidelines for social science data from Massachusetts Institute of Technology's (MIT) Social Science Data Services (30/9/2010)

Many online repositories or data centres provide guidelines on how to cite the data that they maintain and provide e.g., which provides specific types of data sets, often repeating over time, provides thorough guidelines on citing each electronic release of census data and related studies.

The UK Data Archive, which houses a wider variety of data sets, includes general data citation advice in an FAQ (How do I acknowledge and cite data?), and includes the specific citation information for each data set when you download it.

In February 2014 the Data Citation Synthesis Group released the Joint Declaration of Data Citation Principles.