Data Management Plans: Implications for Automated Analyses

Authors : Ngoc-Minh Pham, Heather Moulaison-Sandy, Bradley Wade Bishop, Hannah Gunderman

Data management plans (DMPs) are an essential part of planning data-driven research projects and ensuring long-term access and use of research data and digital objects; however, as text-based documents, DMPs must be analyzed manually for conformance to funder requirements.

This study presents a comparison of DMPs evaluations for 21 funded projects using 1) an automated means of analysis to identify elements that align with best practices in support of open research initiatives and 2) a manually-applied scorecard measuring these same elements.

The automated analysis revealed that terms related to availability (90% of DMPs), metadata (86% of DMPs), and sharing (81% of DMPs) were reliably supplied. Manual analysis revealed 86% (n = 18) of funded DMPs were adequate, with strong discussions of data management personnel (average score: 2 out of 2), data sharing (average score 1.83 out of 2), and limitations to data sharing (average score: 1.65 out of 2).

This study reveals that the automated approach to DMP assessment yields less granular yet similar results to manual assessments of the DMPs that are more efficiently produced. Additional observations and recommendations are also presented to make data management planning exercises and automated analysis even more useful going forward.

URL : Data Management Plans: Implications for Automated Analyses


Data Services Librarians’ Responsibilities and Perspectives on Research Data Management

Authors : Bradley Wade Bishop, Ashley M. Orehek, Christopher Eaker, Plato L. Smith

This study of data services librarians is part of a series of studies examining the current roles and perspectives on Research Data Management (RDM) services in higher education. Reviewing current best practices provides insights into the role-based responsibilities for RDM services that data services librarians perform, as well as ways to improve and create new services to meet the needs of their respective university communities.


The objectives of this article are to provide the context of research data services through a review of past studies, explain how they informed this qualitative study, and provide the methods and results of the current study.

This study provides an in-depth overview of the overall job responsibilities of data services librarians and as well as their perspectives on RDM through job analyses.


Job analysis interviews provide insight and context to the tasks employees do as described in their own words. Interviews with 10 data services librarians recruited from the top 10 public and top 10 private universities according to the 2020 Best National University Rankings in the US News and World Reports were asked 30 questions concerning their overall job tasks and perspectives on RDM.

Five public and five private data services librarians were interviewed. The interviews were recorded and transcribed. The transcriptions were analyzed in NVivo using a grounded theory application of open, axial, and selective coding to generate categories and broad themes based on the responses using synonymous meanings.

Results: The results presented here provide the typical job tasks of data services librarians that include locating secondary data, reviewing data management plans (DMPs), conducting outreach, collaborating, and offering RDM training. Fewer data services librarians assisted with data curation or manage an institutional repository.


The results indicate that there may be different types of data services librarians depending on the mix of responsibilities. Academic librarianship will benefit from further delineation of job titles using tasks while planning, advertising, hiring, and evaluating workers in this emerging area. There remain many other explorations needed to understand the challenges and opportunities for data services librarians related to RDM.


This article concludes with a proposed matrix of job tasks that indicates different types of data services librarians to inform further study. Future job descriptions, training, and education will all benefit from differentiating between the many associated research data services roles and with increased focus on research data greater specializations will emerge.

URL : Data Services Librarians’ Responsibilities and Perspectives on Research Data Management


The Data Life Aquatic: Oceanographers’ Experience with Interoperability and Re-usability: Oceanographers’ Experience with Interoperability and Re-usability

Authors : Bradley Wade Bishop, Carolyn F Hank, Joel T Webster

This paper assesses data consumers’ perspectives on the interoperable and re-usable aspects of the FAIR Data Principles. Taking a domain-specific informatics approach, ten oceanographers were asked to think of a recent search for data and describe their process of discovery, evaluation, and use.

The interview schedule, derived from the FAIR Data Principles, included questions about the interoperability and re-usability of data. Through this critical incident technique, findings on data interoperability and re-usability give data curators valuable insights into how real-world users access, evaluate, and use data.

Results from this study show that oceanographers utilize tools that make re-use simple, with interoperability seamless within the systems used. The processes employed by oceanographers present a good baseline for other domains adopting the FAIR Data Principles.

URL : The Data Life Aquatic: Oceanographers’ Experience with Interoperability and Re-usability: Oceanographers’ Experience with Interoperability and Re-usability