Challenges in tracking archive’s data reuse in social sciences

Purpose Identifying data reuse is challenging, due to technical reasons, and, in particular, incorrect citation practices among scholars. This paper aims to propose an automatic method to track the reuse of data deposited in the archives joined to the CESSDA (Consortium of European Social Science Data Archives) infrastructure. The paper also offers an overview on the identified data to understand the characteristics of the most reused data sets. Design/methodology/approach The reuse of data sets stored in the GESIS data archive, the biggest CESSDA data archive, and cited in publications indexed by Scopus, is tracked. Metadata of publications, and those of data sets, allow us to understand the characteristics and circumstances in which data reuse happens. Findings This contribution demonstrates the possibility of tracking data reuse through an automatic way, despite the technical difficulties in doing it. Evidence about the most reused data are shown, highlighting some limits in the tracking practices of reuse. Finally, some suggestions to the actors involved in data sharing are proposed. Originality/value The originality of this work is the provision of an automatic procedure to investigate and measure the data reuse, providing information on how it happens. This is uncommon in the social science literature and archives, that usually adopt inaccurate metrics to measure data reuse.