Skip to main content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Data & Statistics Research Guide

Why Cite Data and Software?

Much like journal articles, data and software are research products. Research takes time and a lot of hard work, so by citing a researcher's data or software, you are giving them their due credit and also increasing the quality of your own scholarship by showing what resources you've investigated to form your own conclusions. Generally, citations give credit to the authors or producers of the original work, and they enable readers to locate, identify, and analyze the resources drawn on for their work. 

How to Cite Data and Statistics

Citing data is very similar to citing journal articles, and many style manuals (APA, Chicago, MLA) offer guidance. At minimum, every data citation should include the following:

  • Title
  • Author
  • Date 
  • Version
  • Persistent Identifier (e.g. DOI)
  • Producer or Distributor (often the name of the repository managing the data, e.g. ICPSR or NCBI)

Persistent Identifiers are generally issued by the repository holding the data and include such identifiers as: Digital Object Identifier (DOI), Globally Unique Identifier (GUID), Archival Resource Key (ARK), Uniform Resource Name (URN), or any identifiers generally based on the Handel System.  URLs are not persistent identifiers but are okay to use in cases when no persistent identifier is provided. 

Examples:

Citation from ICPSR

ICPSR Example Data Citation

APA

ABC News. (2007). ABC News Education Poll, February 1990. (ICPSR version) [data file and codebook]. Radnor, PA: Chilton Research Services [producer]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor]. doi:10.3886/ICPSR09440.v1

Chicago Style

ABC News. 2007. ABC News Education Poll, February 1990. ICPSR version. Radnor, PA: Chilton Research Services. Distributed by Ann Arbor, MI: Inter-university Consortium for Political and Social Research. doi:10.3886/ICPSR09440.v1.

MLA

ABC News. ABC News Education Poll, February 1990. ICPSR version. Radnor, PA: Chilton Research Services [producer]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2007-01-26. Web. 11 Mar 2015. doi:10.3886/ICPSR09440.v1

This information has been adapted from the IASSIST Quick Guide to Data Citation and the MSU How to Cite Data Research Guide.

How to Cite Software Packages

The Principles of Data Citation

The Principles of Data Citation from Force 11 Working Group (abridged):

  • Data are important to the scholarly record
  • Researchers and other data producers deserve credit for their work
  • Data serve as evidence to support claims
  • Data should be uniquely identified so that they can be cited clearly (e.g. DOI)
  • The citation should be clear and long-lasting even if the data are not

Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. Martone M. (ed.) San Diego CA: FORCE11; 2014 https://doi.org/10.25490/a97f-egyk

The Principles of Software Citation

The Principles of Software Citation from Force 11 Working Group (abridged):

  • Software is important to the scholarly record
  • Developers of the code and software credit and recognition for their work
  • Software should be uniquely identified in order be cited clearly (e.g. include a DOI)
  • The citation should be clear and long-lasting even if the software is not
  • The citation should help a reader find and access the software 
  • It should be precise enough to allow a reader to identify the exact version of the software used

Smith AM, Katz DS, Niemeyer KE, FORCE11 Software Citation Working Group. (2016) Software citation principles. PeerJ Computer Science 2:e86 https://doi.org/10.7717/peerj-cs.86

GW Libraries • 2130 H Street NW • Washington DC 20052202.994.6558AskUs@gwu.edu