Researchers should cite data when communicating their scholarly or scientific findings in the same way that they cite articles, books, and other sources. Data citation gives credit and attribution to the creator, encourages sharing, collaboration, and re-use, enables verification of research results, and allows for tracking usage and impact. Data takes many forms across academic disciplines. Some of these include:
Although uniform citation formats have been slow to develop, below are the commonly accepted elements of data citation:
When citing data for publication, below are a number of places researchers can look for guidance:
Below are several citation styles. Under each style is an example citation.
Leiss, Amelia. 1999. “Arms Transfers to Developing Countries, 1945–1968.” Inter-University Consortium for Political and Social Research, Ann Arbor, MI. ICPSR05404-v1. https://doi.org/10.3886/ICPSR05404.
Deschenes, Elizabeth Piper, Susan Turner, and Joan Petersilia. Intensive Community Supervision in Minnesota, 1990–1992: A Dual Experiment in Prison Diversion and Enhanced Supervised Release [Computer file]. ICPSR06849-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2000. (https://doi:10.3886/ICPSR06849)
Andrikou C, Thiel D, Ruiz-Santiesteban JA, Hejnol A. Active mode of excretion across digestive tissues predates the origin of excretory organs. 2019. Dryad Digital Repository. https://doi.org/10.5061/dryad.bq068jr.
O’Donohue, W. (2017). Content analysis of undergraduate psychology textbooks (ICPSR 21600; Version V1) [Data set]. ICPSR. https://doi.org/10.3886/ICPSR36966.v1
1. GenBank (for RP11-322N14 BAC [accession number AC087526.3]; accessed April 6, 2016), http://www.ncbi.nlm.nih.gov/nuccore/19683167.
GenBank (for RP11-322N14 BAC [accession number AC087526.3]; accessed April 6, 2016). http://www.ncbi.nlm.nih.gov/nuccore/19683167.
 C. J. Brothers, J. Harianto, J. B. McClintock, and M. Byrne, “Data from: Sea urchins in a high-CO2 world: the influence of acclimation on the immune response to ocean warming and acidification.” (Aug. 3rd, 2016). Distributed by Dryad Digital Repository. doi: 10.5061/dryad.9hr7t (accessed July 4th, 2019).
Lee, John D.; Alsaid, Areen, 2020, "A Machine Vision Approach for Estimating Motion Discomfort in Simulators and in Self-Driving", https://doi.org/10.7910/DVN/ZHGT7U, Harvard Dataverse, V1