Approaches to Data Sharing: An Analysis of NSF Data Management Plans from a Large Research University
INTRODUCTION Sharing digital research data is increasingly common, propelled by funding requirements, journal publishers, local campus policies, or community-driven expectations of more collaborative and interdisciplinary research environments. However, it is not well understood how researchers are addressing these expectations and whether they are transitioning from individualized practices to more thoughtful and potentially public approaches to data sharing that will enable reuse of their data. METHODS The University of Minnesota Libraries conducted a local opt-in study of data management plans (DMPs) included in funded National Science Foundation (NSF) grant proposals from January 2011 through June 2014. In order to understand the current data management and sharing practices of campus researchers, we solicited, coded, and analyzed 182 DMPs, accounting for 41% of the total number of plans available. RESULTS DMPs from seven colleges and academic units were included. The College of Science of Engineering accounted for 70% of the plans in our review. While 96% of DMPs mentioned data sharing, we found a variety of approaches for how PIs shared their data, where data was shared, the intended audiences for sharing, and practices for ensuring long-term reuse. CONCLUSION DMPs are useful tools to investigate researchers’ current plans and philosophies for how research outputs might be shared. Plans and strategies for data sharing are inconsistent across this sample, and researchers need to better understand what kind of sharing constitutes public access. More intervention is needed to ensure that researchers implement the sharing provisions in their plans to the fullest extent possible. These findings will help academic libraries develop practical, targeted data services for researchers that aim to increase the impact of institutional research.
External Data or Supplements:
Bishoff, Carolyn; Johnston, Lisa, 2015, “Instrument used to code DMPs”, http://dx.doi.org/10.7910/DVN/5JGNMM, Harvard Dataverse. [Instrument]
Johnston, Lisa R; Bishoff, Carolyn; McGrory, John; Storino, Chris; Swendsrud, Anders. (2015). Analyzed Data Management Plans (DMPs) from Successful University of Minnesota Grants from the National Science Foundation, 2011-2014 [dataset]. Retrieved from the Data Repository for the University of Minnesota, http://dx.doi.org/10.13020/D6TG6Z [Data]
How to Cite:
Bishoff, C. & Johnston, L., (2015) “Approaches to Data Sharing: An Analysis of NSF Data Management Plans from a Large Research University”, Journal of Librarianship and Scholarly Communication 3(2), p.eP1231. doi: https://doi.org/10.7710/2162-3309.1231