An Insider’s Take on Data Curation: Context, Quality, and Efficiency
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.
Keywords: data curation, quality, automation, scripts, archives, social science data, DCN
How to Cite:
Hawthorne, S., (2021) “An Insider’s Take on Data Curation: Context, Quality, and Efficiency”, Journal of eScience Librarianship 10(3): 1. doi: https://doi.org/10.7191/jeslib.2021.1200
Rights: © 2021 Hawthornee. This is an open access article licensed under the terms of the Creative Commons Attribution License.