Toward a conceptual framework for data sharing practices in social sciences: A profile approach

Abstract

© 2016 Wei Jeng, Daqing He, and Jung Sun Oh This paper investigates the landscape of data-sharing practices in social sciences via the data sharing profile approach. Guided by two pre-existing conceptual frameworks, Knowledge Infrastructure (KI) and the Theory of Remote Scientific Collaboration (TORSC), we design and test a profile tool that consists of four overarching dimensions for capturing social scientists' data practices, namely: 1) data characteristics, 2) perceived technical infrastructure, 3) perceived organizational context, and 4) individual characteristics. To ensure that the instrument can be applied in real and practical terms, we conduct a case study by collecting responses from 93 early-career social scientists at two research universities in the Pittsburgh Area, U.S. The results suggest that there is no significant difference, in general, among scholars who prefer quantitative, mixed method, or qualitative research methods in terms of research activities and data-sharing practices. We also confirm that there is a gap between participants' attitudes about research openness and their actual sharing behaviors, highlighting the need to study the “barrier” in addition to the “incentive” of research data sharing.