(219h) A Graduate Course in Research Data Management

Effective practices in research data management (RDM) are require because it leads to thorough and thoughtful use of the data for sharing and publication and it had become a required part of research funded by federal organizations. The National Academy of Science (NAS) has advocated for the development of standards and policies regarding the dissemination and management of data, and data management for all researchers.[1] As a practical result, training in and knowledge of RDM is critical for future researchers.

Literature studies have shown that faculty understand the need for RDM education for their students and would benefit from experts providing guidance.[2] Faculty have also observed that graduate students were not prepared to effectively manage data, but the faculty also acknowledge that they cannot provide adequate guidance or instruction.[3] Thus it is evident that graduate students need to be provided with education on RDM to meet funding requirements and also succeed in research. However, the ability of the research faculty to provide this education is not present.

In this work, we present a graduate course in Research Data Management for students in research fields. This course is designed to provide in-depth knowledge that the NAS and NSF encourage for graduate students. This course was co-taught by a librarian/information specialist and a research active faculty member. This teaching arrangement benefited the students as the librarian delivered knowledge on RDM tools and standards while allowing the faculty member to provide research focused examples and real-life experiences. This presentation will describe the course, course materials, lecture topics, student work as well as lessons learned.

Research Data Management was taught as a 3 credit graduate course during Fall semester 2016. The course was taught as an elective and had no pre-requisites. Ten graduate student enrolled in the course. ”Data Management for Researchers” by Kristen Briney was used as the textbook. Pre- and post-course assessment was performed to determine the students’ knowledge about specific areas of RDM.

The class schedule and individual lecture topics will be presented. The individual lecture topics were in three areas: 1) broad concepts of RDM, 2) examples of specific concepts in RDM as demonstrated by guest experts, and 3) focused application of RDM to ongoing research projects. Specific RDM tools such as DMPtool were incorporated into the course. Student work also fell into three areas: 1) individual assignments to reinforce lecture topics, 2) student reflections on guest speaker topics with potential applications to the student’s research, and 3) generation of a Data Curation Profile (DCP) as a final project.

The benefits and drawbacks of co-teaching the course between a librarian and researcher will be discussed. Advantages of a for-credit course compared to non-credit workshops will be presented. Alternative approaches for graduate RDM education will also be suggested. Use of small groups for preparing the DCP final project allowed for development of a complete DCP while also balancing the required student effort. Use of outside speakers allowed for the introduction of specific examples and expertise from a broad array of campus experts. Assessment also demonstrated significant student knowledge gain in each area examined. Student feedback will also be presented and discussed.

References:

1. Committee on Ensuring the Utility and Integrity of Research Data in a Digital Age; National Academy of Sciences, Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age, The National Academy Press, Washington, D.C., 2009
2. McLure, M., et al., Data Curation: A Study of Researcher Practices and Needs. Portal: Libraries and the Academy, 2014. 14(2): p. 139-164.
3. National Science Foundation, Proposal and Award Policies and Procedures Guide Part I - Grant Proposal Guide, N.S. Foundation, Editor 2013.