What is data citation?
Data citation refers to the practice of providing a reference to data in the same way as researchers routinely provide a bibliographic reference to outputs such as journal articles, reports and conference papers. Citing data is now recognised as one of the key practices leading to recognition of data as a primary research output. This is important because:
- Evidence suggests that citing data in related publications increases the citation rate of those publications
- Routine citation of data acknowledges data as a first class research output and facilitates reproducible and transparent research
- Citations for published data can be included in CVs and biographical sketches along with journal articles, reports and conference papers
- Only cited data can be counted and tracked (in a similar manner to journal articles) to measure impact.
Data Citation for institutions: explores key issues, policies on DOIs (granularity, versioning etc), case studies, integration of data into scholarly communications, reward for data citation.
Data Citation for researchers: explores planning to publish data, creating published data, citing your own and other’s data, finding out about who is reusing your data, how to augment your profiles using data citation.
Citing research data
Published research data can be cited in the same way as other scholarly outputs. Styles and formats for data varies in the same way article citation styles and formats vary. Important elements in citing data, regardless of citation style, publisher or repository guidelines can be found in this short Overview by Purdue University.
A standard citation would include the following elements:
Author(s) (Year) : Title. Publisher(s). DOI(if used)
Hanigan, Ivan (2012): Monthly drought data for Australia 1890-2008 using the Hutchinson Drought Index. The Australian National University Australian Data Archive.
The ANDS Guide to Data Citation offers advice on:
- Data citation styles and formats - with and without a DOI
- Data repositories: styles and formats
- Journals: data citation styles and formats
- Data citation elements for repository managers
ANDS and data citation
- engaging with research funding agencies to promote data publication as a primary research output and the inclusion of data in the research assessment process
- working with Thomson Reuters Data Citation Index to track and record data citations as part of research assessment activities
- contributing to international initiatives through the Research Data Alliance aimed at improving data citation and tracking
- offers a DOI Service to assign DOIs to datasets and collections.
More information about ANDS services: firstname.lastname@example.org
Hands on learning about data citation
Citation analysis and citation metrics are important to the academic community. Find out where data fits in the citation picture.
- Getting started: how to cite data
- Learn more: may the Force(11) be with you (while you cite data)
- Challenge me: are some data formats more likely to be cited?
What are Digital Object Identifiers (DOIs) and how do they support data citation and metrics for data and related research objects?
- Getting started: what are DOIs and why are they critical for accurate citation metrics?
- Learn more: delves into altmetrics (and donuts!)
- Challenge me: what about enabling citation through DOIs for software, algorithms and grey literature?