Most researchers are 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, it is appropriate to credit them for it
- if using personally created data, providing access to this will allow others to re-use and cite it
- access to the raw data may facilitate validation of the research
Many journals, data centres and repositories may have their own preferred styles, so you should consult their specific guidance on citing data.
DataCite is an international organisation founded in London in 2009.
It organises workshops to promote good practice, manages a metadata schema (pdf) for citation, and issues DOIs - unique digital object identifiers which will reliably link to the data even in the repository in which it resides changes.
How is data cited?
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
Publisher: the data centre or repository
Resource type: to facilitate accessing the data
Identifier: locational information i.e. a URL or preferably a DOI