Social science data repositories in data deluge: A case study of ICPSR's workflow and practices

Purpose Owing to the recent surge of interest in the age of the data deluge, the importance of researching data infrastructures is increasing. The open archival information system (OAIS) model has been widely adopted as a framework for creating and maintaining digital repositories. Considering that OAIS is a reference model that requires customization for actual practice, this paper aims to examine how the current practices in a data repository map to the OAIS environment and functional components. Design/methodology/approach The authors conducted two focus-group sessions and one individual interview with eight employees at the world’s largest social science data repository, the Interuniversity Consortium for Political and Social Research (ICPSR). By examining their current actions (activities regarding their work responsibilities) and IT practices, they studied the barriers and challenges of archiving and curating qualitative data at ICPSR. Findings The authors observed that the OAIS model is robust and reliable in actual service processes for data curation and data archives. In addition, a data repository’s workflow resembles digital archives or even digital libraries. On the other hand, they find that the cost of preventing disclosure risk and a lack of agreement on the standards of text data files are the most apparent obstacles for data curation professionals to handle qualitative data; the maturation of data metrics seems to be a promising solution to several challenges in social science data sharing. Originality/value The authors evaluated the gap between a research data repository’s current practices and the adoption of the OAIS model. They also identified answers to questions such as how current technological infrastructure in a leading data repository such as ICPSR supports their daily operations, what the ideal technologies in those data repositories would be and the associated challenges that accompany these ideal technologies. Most importantly, they helped to prioritize challenges and barriers from the data curator’s perspective and to contribute implications of data sharing and reuse in social sciences.