Data citation refers to the practice of providing a reference to data in the same way as bibliographic reference is routinely provided to other scholarly resources.
Citing bibliographical references (journal papers, books, dissertations, reports, etc.) when performing and writing your own research work is a standard practice. As a norm, research work is based on different types of data:
- In some cases it is original data produced in different ways and methods by yourself, the researcher.
- However, in vast majority of cases it is (at least partially) data provided by other researchers or obtained from existing, published sources.
The latter holds true especially for materials research where data underlying the findings and subsequent published scientific work is crucial.
Driven by publisher and funding bodies’ requirements for reproducible research and reusable research outputs, data has come to be regarded as a primary research output rather than a by-product of research.
When datasets are cited, they become:
- discoverable,
- reusable, and
- citable by others.
Citation of data also enables recognition of scholarly effort in disciplines and organisations that want to acknowledge and reward data outputs.
(Source: Australian National Data Service website (www.ands.org.au). Accessed 09 April 2018.)