Citing data and software: a key to recognition as a primary research output.
It is now considered ‘best practice’ to provide a reference to data and software in the same way as researchers routinely provide a bibliographic reference to outputs such as journal articles, reports and conference papers. Citing data and software is one of the key practices leading to recognition of data and software as a primary research output.
The citation of data and software is essential as:
- it acknowledges data and software as a first class research output and facilitates reproducible and transparent research.
- provides credit for those who spend time developing software or collecting, manipulating and analysing research data.
- citations for published data and software can be included in journal articles, reports and conference papers as well as CVs.
- citing data and software in related publications may increase their citation rate.
- cited data and software can be counted and tracked (in a similar manner to journal articles) to measure impact.
How to cite research data and software
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. Below are examples of what elements a standard data citation and software citation should include:
Standard data citation
Creator (PublicationYear): Title. Publisher. (resourceTypeGeneral). Identifier
Hanigan, Ivan (2012): Monthly drought data for Australia 1890-2008 using the Hutchinson Drought Index. The Australian National University Australian Data Archive. (Dataset) http://doi.org/10.4225/13/50BBFD7E6727A
Standard software citation
Creator (PublicationYear): Title. Version No. Publisher. [resourceTypeGeneral]. Identifier.
Xu, C., & Christoffersen, B. (2017). The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States). [Software]. https://doi.org/10.11578/dc.20171025.1962
How ARDC supports data and software citation
We do this in a number of ways, including:
- Working with research funding agencies to promote data and software as primary research outputs that should be included in the research assessment process.
- Working with Clarivate Data Citation Index to track and record data and software citations as part of research assessment activities.
- Contributing to international initiatives through the Research Data Alliance aimed at improving data and software citation and tracking.
- Offering a DOI Service to assign DOIs to datasets, software and collections.
- Offering the 23 (research data) Things program, which includes two activities about data citation Thing 7: Data citation for access & attribution and Thing 8: Citation metrics for data.
- ARDC’s 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 and data citation elements for repository managers.
- Data Citation for institutions which explores key issues, policies on DOIs (granularity, versioning etc), case studies, integration of data into scholarly communications, reward for data citation.
Your data & software citation toolkit
We’ve put together a list of handy guides and tools to help you ensure you’re always up to date on best practices for using identifiers and citations.