Influence of Academic Rank on Faculty Members' Attitudes Toward Research Data Management
Session Type: Research Update
Session Description
Academic librarians are increasingly engaging in data curation by providing
infrastructure (e.g., institutional repositories) and offering services (e.g.,
consultation on data management planning) to support the management of
research data on their campuses. Efforts to develop these resources can
benefit from a greater understanding of the social factors that affect how
researchers manage their data and whether they choose to preserve their data
long-term or openly share their data. In particular, academic rank is often
thought to be an important factor influencing researchers’ attitudes to data
preservation and sharing. This possibility, however, has rarely been directly
investigated. In this research project, we analyzed the results of our recent
campus-wide survey of research data management practices and perspectives,
which encompassed arts & humanities, social sciences, and natural sciences
faculty members, by categorizing the respondents into professor, associate
professor, assistant professor, and non-tenure-track ranks. We found
statistically significant differences among faculty ranks in familiarity with
funding agency requirements for data management plans, reasons that might
prevent data sharing, and interest in data management-related services. No
differences among faculty ranks, however, were observed for the amount of
research data being stored, types of storage media, likelihood or openness of
data sharing, use of data repositories/archives, or familiarity with data
documentation. These findings reveal some key distinctions among different
ranks of faculty members in their actions and attitudes toward research data
management. Serious consideration of both the similarities and dissimilarities
among academic ranks will help guide librarians and data curation
professionals in developing data management-related services that are tailored
to different researchers. Instead of a “one size fits all” approach, the most
effective approach to data curation may be one that is tailored to the unique
needs of specific populations of researchers.
Session Leaders
Katherine G. Akers, Emory University Libraries
Jennifer Doty, Emory University Libraries
View the community reporting Google doc for this session.