A Reputation Economy: Results from an Empirical Survey on Academic Data Sharing

1454 Deutsches Institut für Wirtschaftsforschung 2015 Opinions expressed in this paper are those of the author(s) and do not necessarily reflect views of the institute. Acknowledgement We thank Gert G. Wagner and Mathis Fräßdorf for their helpful comments and suggestions. We thank Klaus Tochtermann and the Leibniz Science 2.0 Research Association for support. We gratefully acknowledge the financial support from the German Research Foundation (DFG) under the project " European Data Watch Extended " (PI: Gert G. Wagner, DFG-Grant Number WA 547/6-1). Abstract: Academic data sharing is a way for researchers to collaborate and thereby meet the needs of an increasingly complex research landscape. It enables researchers to verify results and to pursuit new research questions with " old " data. It is therefore not surprising that data sharing is advocated by funding agencies, journals, and researchers alike. We surveyed 2661 individual academic researchers across all disciplines on their dealings with data, their publication practices, and motives for sharing or withholding research data. The results for 1564 valid responses show that researchers across disciplines recognise the benefit of secondary research data for their own work and for scientific progress as a whole—still they only practice it in moderation. An explanation for this evidence could be an academic system that is not driven by monetary incentives, nor the desire for scientific progress, but by individual reputation—expressed in (high ranked journal) publications. We label this system a Reputation Economy. This special economy explains our findings that show that researchers have a nuanced idea how to provide adequate formal recognition for making data available to others—namely data citations. We conclude that data sharing will only be widely adopted among research professionals if sharing pays in form of reputation. Thus, policy measures that intend to foster research collaboration need to understand academia as a reputation economy. Successful measures must value intermediate products, such as research data, more highly than it is the case now.