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Data requires citations for the same reasons journal articles and other types of publications require citations: to acknowledge the original author/producer and to help other researchers find the resource.
Citing data is important because it:
- Acknowledges and provides credit to the originator of the data
- Allows verification of data and results, facilitating their re-use in further research
- Enables data citation metrics (the impact of data) to be tracked.
Data citation has benefits for researchers as it:
- Makes data publications more acceptable for CVs and journals
- Facilitates discovery of grey literature.
Benefits of Citing Data, source: Australian National Data Service
Components of a Dataset Citation
At minimum, these elements should be present in any dataset citation:
- Author (creators of the dataset)
- Title (of the dataset)
- Publication date (of the dataset)
- Publisher (name of repository where the data is published)
- Version number (of the dataset, if any)
- Location (URL / DOI to access the dataset)
The way these elements would be arranged, or combined together in the finished citation, would depend on the citation style requirements of the publisher.
Quick Guides to Data Citation
Citation software helps you to:
- import citations from your favorite databases and websites.
- build and organize bibliographies.
- format citations for papers.
- take notes on articles and save them in your collection of citations.
- save and organize PDFs, screenshots, graphs, images, and other files for your research.