Social Scientists’ Data Reuse Principally Influenced by Disciplinary Norms, Attitude, and Perceived Effort

Abstract

A Review of:
 Yoon, A. & Kim, Y. (2017). Social scientists’ data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories. Library & Information Science Research, 39(3), 224–233. https://doi.org/10.1016/j.lisr.2017.07.008
 Abstract
 Objective – To propose and test a model grounded in constructs from psychology and information systems to explain data reuse behaviours and practices in the social sciences.
 Design – Electronic survey.
 Setting – ProQuest’s Community of Science Scholars database.
 Subjects – Included 2,193 randomly selected social scientists associated with U.S. academic institutions.
 Methods – An electronic survey was distributed to a random sample of U.S.-based social science scholars from ProQuest’s Community of Science Scholars database. The survey adapted 21 measurement items for constructs taken from the theory of planned behaviour (TPB) and the technology acceptance model (TAM), including perceived usefulness, perceived effort, and the subjective norm surrounding data reuse.
 Main Results – There were 292 valid responses received, giving a response rate of 14.91%. Survey data largely validated the authors’ theoretical model. Attitudinal, normative, and resource factors all influence social scientists’ intended data reuse. In particular, perceived usefulness of reusing data and subjective norms surrounding data reuse in one’s discipline positively correlate with intentions to reuse data, and perceived concern of reusing data negatively correlate with intentions to reuse data.
 Conclusion – Data reuse in the social sciences is influenced by the perceptions and beliefs held by social scientists. Social scientists reuse others’ data when they perceive that doing so would improve their research productivity and when their discipline has strong norms of data reuse. They avoid reusing others’ data when they believe that doing so is problematic (e.g., if they believe reusing infringes on copyright). Supporters of data sharing, including librarians, are encouraged to apply these findings by proactively educating researchers on the benefits, potential obstacles, and methods of data reuse.