Promoting sustainable research practices through effective data management curricula

Abstract

Managing research data effectively is critical to producing high quality datasets that support data preservation, sharing, reuse, and reproducible research. Academic librarians are increasingly playing a role in providing training and education in data management (DM) for faculty and students. While emerging data management curricula are converging on a common set of topics covered, expected learning outcomes, instructional materials, techniques and strategies still vary widely. This wide variability in DM instructional approaches largely reflects the similarly broad variety of audiences for the material, and the instructors offering it. The audience for DM instruction includes graduate students, faculty and research support staff from all disciplines, liaison librarians, data specialists and many others. Instructional methods range from online modules and coursework, workshops, and credit-bearing courses. There is no one-size-fits-all approach to teaching data management, so having a familiarity with the variety of teaching models and methods currently being used is very helpful in designing a teaching strategy that is targeted to your audience.

Librarians from three public research universities will describe their developing DM teaching programs, including a credit-bearing graduate course, a workshop series for librarians, and a workshop series for graduate students, research support staff, and investigators. In support of establishing best practices for data management instruction, we will describe successes and challenges in delivery, retention, and customizing materials for particular audiences. We will also compare instructional design, activities, and assessment approaches to identify common, effective strategies across all three. We will invite the audience to guide the panel discussion through a series of group polls.