Research Guides

Research Data Management (Health Sciences)

Tips for managing data and creating a data management/sharing plan.

Why cite data?

Just as it's important to cite previous research, it's equally important to cite datasets. By citing data, you increase the transparency of your own work while giving credit to the original data producers. 

How to cite data?

Data citations consist of similar elements as standard citations. These include:

  • Author (the creator of the dataset)
  • Date (the date when the dataset was published or otherwise made available)
  • Title (the name of the dataset)
  • Publisher (the entity that makes the dataset available, such as the name of a data repository)
  • Digital location (ideally a digital object identifier (DOI) but could also be a web address)

You should expect some variation, including added elements, depending on journal citation specifications or style. 

Although data citation practices are still emerging, you should cite datasets in your References section. This will make it easier for others to find the dataset, while also ensuring that its use is captured correctly in the scholarly record.

Why Cite Diverse Voices?

Citation is widely used as a metric for evaluating performance in Western academia. Like other cultural practices, citation is susceptible to biases that reflect and reinforce dominant historical power structures of race, gender, and class.

Citation justice is the practice of maintaining an awareness of these biases and actively working to build more inclusive and equitable citation networks within your works. By choosing to cite scholars with varied backgrounds and identities, you intentionally expand the academic conversation, and increase equity and inclusion in your fields.

Some suggestions for inclusive citation practice include:

  • Experiment with search terms and sources, and broaden your reading: reading from a range of cultures, races, and other identities can help diversify citations. 
  • Audit your citation list. Does it include racialized, female-identified, early-career, or non-academic authors?
  • Include a citation diversity statement to increase the transparency of your practice and encourage other scholars to do likewise.

Interested in learning more about citation justice?

Courtesy: Reiman-Sendi KA, Citation Help, available at https://guides.lib.umich.edu/citationhelp

Data Citation Examples

U-M Deep Blue Data

Almazroa, A. (2018). Retinal fundus images for glaucoma analysis: the RIGA dataset [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/Z23R0R29

ICPSR

Harris, Kathleen Mullan, and Udry, J. Richard. National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2018 [Public Use]. Carolina Population Center, University of North Carolina-Chapel Hill [distributor], Inter-university Consortium for Political and Social Research [distributor], 2022-08-09. https://doi.org/10.3886/ICPSR21600.v25 

APA Style

Smith, T.W., Marsden, P.V., & Hout, M. (2011). General social survey, 1972-2010 cumulative file (ICPSR31521-v1) [data file and codebook]. Chicago, IL: National Opinion Research Center [producer]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor]. doi: 10.3886/ICPSR31521.v1

Chicago Style

Smith, Tom W., Peter V. Marsden, and Michael Hout. 2011. General Social Survey, 1972-2010 Cumulative File. ICPSR31521-v1. Chicago, IL: National Opinion Research Center. Distributed by Ann Arbor, MI: Inter-university Consortium for Political and Social Research. doi:10.3886/ICPSR31521.v1

MLA Style 

Smith, Tom W., Peter V. Marsden, and Michael Hout. General Social Survey, 1972-2010 Cumulative File. ICPSR31521-v1. Chicago, IL: National Opinion Research Center [producer]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2011. Web. 23 Jan 2012. doi:10.3886/ICPSR31521.v1

Last Updated: Sep 23, 2025 12:04 PM
Subjects: Health Sciences