A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository
Pienta, Amy M., Dharma Raell Akmon, Justin Ryan Noble, Lynette Hoelter, and Susan Jekielek. 2018. "A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository." International Journal of Digital Curation, 2017(12): 2.
Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users' search activity in an established social science data repository to better understand demand for data and more effectively guide collection development. By applying a data-driven approach, we aim to ensure curation resources are applied to make the most valuable data findable, understandable, accessible, and usable. We analyze data from a domain repository for the social sciences that includes over 500,000 annual searches in 2014 and 2015 to better understand trends in user search behavior. Using a newly created search-to-study ratio technique, we identified gaps in the domain data repository's holdings and leveraged this analysis to inform our collection and curation practices and policies. The evaluative technique we propose in this paper will serve as a baseline for future studies looking at trends in user demand over time at the domain data repository being studied with broader implications for other data repositories.