Data Sharing Among Ecology, Evolution, and Natural Resources Scientists: An Analysis of Selected Publications: Journal of Librarianship and Scholarly Communications 3(2)

A new article from the Journal of Librarianship and Scholarly Communications 3(2)

Abstract information follows.

Data Sharing Among Ecology, Evolution, and Natural Resources Scientists: An Analysis of Selected Publications

Authors: Philip Herold Abstract

INTRODUCTION

Understanding the differing data management practices among academic disciplines is an important way to inform existing and emerging library research support and services. This paper reports findings from a study of data sharing practices among ecology, evolution, and natural resources scientists at the University of Minnesota. It examines data sharing rates, methods, and disciplinary differences and discusses the characteristics of researchers, data, methods, and aspects of data sharing across this group of disciplines.

METHODS

Data sharing practices are investigated by reviewing the two most recently published research articles (n=155) for each faculty member (n=78) in three departments at a single large research university. All mentions of data sharing in each publication were pursued in order to locate, analyze, and characterize shared data.

RESULTS

Seventy-two of 155 (46%) articles indicated that related research data was publicly shared by some method. The most prevalent method for data sharing was via journal websites, with 91% of data sharing articles using this method. Ecology, evolution, and behavior scientists shared data at the highest rate (70% of their articles), contrasting with fisheries, wildlife, and conservation biologists (18%), and forest resources (16%).

DISCUSSION

Differences between data sharing practices may be attributable to a range of influences: funder, journal, and institutional policies; disciplinary norms; and perceived or real rewards or incentives, as well as contrasting concerns, cost, or other barriers to sharing data.

CONCLUSION

Study results suggest differential approaches to data services outreach based on discipline and research type and support the need for education and influence on both scientist and journal practices.