Researchers will be familiar with the importance of citing references to written material in their research articles. The same principles apply to data:
- if using data produced by someone else, then it is appropriate to give them credit for this
- if using personally created data, then providing access to this will allow others to re-use and cite it
- additionally, access to the raw data may facilitate validation of the research
How is data cited?
DataCite is an international organisation founded in London in 2009 with the aim of 'establishing easier access to research data'.
It organises workshops to promote good practice, it manages a metadata scheme for citation and issues DOIs - unique digital object identifiers which will reliably link to the data even if the repository in which it resides changes.
Example of data citation
As with citations of written articles, there are variations in the style and format of data citations. The following format is one example: Creator, (publication year), title, version, publisher, resource type, identifier.
- Creator: Author or researcher
- Publication year: the date when the dataset was published, rather than when it was created
- Title: self explanatory
- Publisher: the data centre of repository
- Resource type: to facilitate accessing the data
- Identifier: locational information, i.e. a URL or preferably a DOI
An example from DataCite:
Irino, T; Tada, R (2009). Chemical and mineral compositions of sediments from ODP site 127-797. Geological Institute, University of Tokyo. http://dx.doi.org/10.1594/PANGAEA.726855
Alternative general guidelines
- The How to Cite Data page by the Michigan State University Libraries
- Citing Data by the University of Oregon
- Citing Data from the Social Sciences Data Services at the Massachusetts Institute of Technology
Many journals, data centres and repositories may have their own preferred styles and you should consult their specific guidance on how to cite data. For example, the UK Data Archive has specific Terms and Conditions