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

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