2015/03/02 by Benedikt Fecher, Sascha Friesike, Fecher, Benedikt +7 · 1 citation
Computer Science · Decision Sciences · #Research Data Management Practices #scientometrics and bibliometrics research #Scientific Computing and Data Management
paper · pdf · doi:10.48550/arxiv.1503.00481
Academic data sharing is a way for researchers to collaborate and thereby\nmeet the needs of an increasingly complex research landscape. It enables\nresearchers to verify results and to pursuit new research questions with "old"\ndata. It is therefore not surprising that data sharing is advocated by funding\nagencies, journals, and researchers alike. We surveyed 2661 individual academic\nresearchers across all disciplines on their dealings with data, their\npublication practices, and motives for sharing or withholding research data.\nThe results for 1564 valid responses show that researchers across disciplines\nrecognise the benefit of secondary research data for their own work and for\nscientific progress as a whole-still they only practice it in moderation. An\nexplanation for this evidence could be an academic system that is not driven by\nmonetary incentives, nor the desire for scientific progress, but by individual\nreputation-expressed in (high ranked journal) publications. We label this\nsystem a Reputation Economy. This special economy explains our findings that\nshow that researchers have a nuanced idea how to provide adequate formal\nrecognition for making data available to others-namely data citations. We\nconclude that data sharing will only be widely adopted among research\nprofessionals if sharing pays in form of reputation. Thus, policy measures that\nintend to foster research collaboration need to understand academia as a\nreputation economy. Successful measures must value intermediate products, such\nas research data, more highly than it is the case now.\n