Article Type


Publication Date





This commentary describes how context, quality, and efficiency guide data curation at the University of Michigan's Inter-university Consortium for Political and Social Research (ICPSR). These three principals manifest from necessity. A primary purpose of this work is to facilitate secondary data analysis but in order to so, the context of data must be documented. Since a mistake in this work would render any results published from the data inaccurate, quality is paramount. However, optimizing data quality can be time consuming, so automative curation practices are necessary for efficiency. The implementation of these principles (context, quality, and efficiency) is demonstrated by a recent case study with a high-profile dataset. As the nature of data work changes, these principles will continue to guide the practice of curation and establish valuable skills for future curators to cultivate.


data curation, quality, automation, scripts, archives, social science data


I would like to thank the ICPSR Director of Curation, Rujuta Umarji, for providing vital information about the organization. I would also like to thank A.J. Million and Sara Lafia (ICPSR) for their feedback on every draft.

Corresponding Author

Skylar Hawthorne, Inter-university Consortium for Political and Social Research at the University of Michigan, 2723 Carnoustie Drive, Okemos, MI 48864, USA; skyd@umich.edu

Rights and Permissions

© 2021 Hawthornee. This is an open access article licensed under the terms of the Creative Commons Attribution License.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.