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Article Type

Full-Length Paper

Publication Date

2018-12-21

Abstract

Data Management Plans (DMPs) are often required for grant applications. But do strong DMPs lead to better data management and sharing practices? Several recent research projects in the Library and Information Science field have investigated data management planning and practice through DMP content analysis and data-management-related interviews. However, research hasn’t yet shown how DMPs ultimately affect data management and data sharing practices during grant-funded research. The research described in this article contributes to the existing literature by examining the impact of DMPs on grant awards and on Principal Investigators’ (PIs) data management and sharing practices. The results of this research suggest the following key takeaways: (1) Most PIs practice internal data management in order to prevent data loss, to facilitate sharing within the research team, and to seamlessly continue their research during personnel turnover; (2) PIs still have room to grow in understanding specialized concepts such as metadata and policies for use and reuse; (3) PIs may need guidance on practices that facilitate FAIR data, such as using metadata standards, assigning licenses to their data, and publishing in data repositories. Ultimately, the results of this research can inform academic library services and support stronger, more actionable DMPs.

The substance of this article is based upon a lightning talk presentation at RDAP Summit 2018.

Keywords

data management plans, research data, data librarianship

Data Availability

Data associated with this article are available from Zenodo at https://doi.org/10.5281/zenodo.2432419.

Acknowledgments

This research was funded by the National Library of Medicine, National Institutes of Health under cooperative agreement number UG4LM012343 with University of Washington. Many thanks are also in order for the work of my outstanding student research assistant, Wangmo Tenzing. The Montana State University HELPS Lab scheduled and transcribed the PI interviews. Figure 3 was created by Laurie Rutemeyer at Montana State University Statistical Consulting and Research Services, which is supported by Institutional Development Awards (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Awards P20GM103474, 5U54GM104944, U54GM115371, and 5P20GM104417.

Corresponding Author

Sara Mannheimer, Montana State University, P.O. Box 173320, Bozeman, MT 59715; sara.mannheimer@montana.edu

Rights and Permissions

Copyright Mannheimer © 2018

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

AppendixA_1155.pdf (498 kB)
Appendix A: Semi-structured interview instrument

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