Archive and share data
Cite data
FORCE11's Data Citation Principles indicate that data should be considered legitimate, citable products of research and should be accorded the same importance in the scholarly record as citations of other research objects, such as publications.
A data citation should try to include the same elements as a publication citation:
- Author
- Publication date
- Title
- Publisher (this is often the archive where it is housed.)
- Edition or version
- Resource type (eg. dataset or database)
- Access information (a URL or other persistent identifier)
Data Citation Generator:
If you have a dataset's DOI, use CrossCite's DOI Citation Formatter to create a data citation for you based on your selected style.
Examples:
Source: DCC
| APA | Cool, H. E. M., & Bell, M. (2011). Excavations at St Peter's Church, Barton-upon-Humber [Data set]. doi:10.5284/1000389 |
|---|---|
| Chicago |
(Footnote) H. E. M. Cool and Mark Bell, Excavations at St Peter’s Church, Barton-upon-Humber (accessed May 1, 2011), doi:10.5284/1000389. (Bibliography) Cool, H. E. M., and Mark Bell. Excavations at St Peter’s Church, Barton-upon-Humber (accessed May 1, 2011). doi:10.5284/1000389 |
Citing software:
Proper attribution and credit of software can also help reproducibility, collaboration and reuse. For more on how to cite software, consult the following:
Katz DS, Chue Hong NP, Clark T et al. Recognizing the value of software: a software citation guide [version 2; peer review: 2 approved]. F1000Research 2021, 9:1257 (https://doi.org/10.12688/f1000research.26932.2)
Research data metrics
Research datasets can be cited like other research outputs, such as articles and books. Find out how to measure the impact of research data on the Library's Research data metrics guide.
