Analyzing Data Management Plans: Where Librarians Can Make a Difference

Abstract

is the research data services manager at the University of Michigan Library. In this role, he explores the application of the theories, principles, and practices of library science beyond the domain of traditional library work. In particular, Carlson seeks to increase the Library's capabilities and opportunities to provide services supporting data-related research. Much of his work is done through direct collaborations and partnerships with research faculty. Carlson is one of the architects of the Data Curation Profiles Toolkit (http://datacurationprofiles.org) developed by Purdue University and the University of Illinois at Urbana-Champaign and is the principal investigator of the Data Information Literacy project (http://datainfolit.org), a collaboration between Purdue University, Cornell University, the University of Minnesota, and the University of Oregon. Analysis of the DMPs shows that the overall quality of DMPs at UM varies greatly. Some common weaknesses in the DMPs are: lack of roles and responsibilities; lack of metadata standards that will be used; and failure to mention intellectual property rights. Analysis of the DMPs also revealed gaps in the librarians' knowledge of DMP requirements. In addition to discussing the findings from this current set of analyses, overall DMP quality from this study is compared to DMP quality found in a similar analysis of engineering DMPs from 2013. Looking toward a future where the outcome of grant proposals may be more dependent on the quality of the DMP, this analysis gives the engineering librarians at UM a foundation for creating a DMP service in the coming year, and can inform other librarians who wish to develop a similar service at their institution.

Quality evaluation of data management plans at a research university

“…To maintain confidentiality of NSF proposal content, the DMPs were secured on a password-protected, internal library server for the duration of the study. The DMPs were evaluated using a modified version of a rubric previously used by researchers at the University of Michigan (Nicholls et al, 2014;Samuel et al, 2015). Our rubric (Appendix 1) consisted of 15 items addressing the inclusion of information requested by the NSF (National Science Foundation, 2014) and other common pieces of information often found in DMPs.…”

“…Recently, the Data Management Plans as a Research Tool (DART) project, led by Rolando et al (2015), developed and tested an evaluation rubric for NSF DMPs to create a robust and standardized assessment tool for DMPs to enable cross-institutional comparisons. An early version of the DART rubric was used by Samuel et al (2015) to assess 29 DMPs from Engineering faculty at the University of Michigan. They found that the overall quality of DMPs varied greatly and identified elements that were often missing from DMPs, including clear roles and responsibilities for data management, metadata standards for describing research data, and policies for protecting intellectual property rights.…”

An Integrated Data Management Plan Instructional Program

“…A number of instructional and training programs for engineering faculty and researchers have been developed and implemented (Carlson et al, 2011;Johnston and Jeffrys, 2014). Many of these programs are built around data management plan assistance (Samuels at al, 2015;Wang and Fong, 2015;Nelson, 2015). Zilinski et al (2014) have developed a program directed at undergraduate STEM students.…”

“…In response to federal grant agency and publisher mandates for data sharing, science and technology libraries have become actively involved in designing and implementing programs to meet the data management needs of researchers (Tenopir et al, 2015;Samuels et al, 2015). Along with these new opportunities comes challenges in establishing effective programs and services that support the data workflow needs of researchers.…”

Research Data Practices of Aerospace Engineering Faculty: A Qualitative Study

“…Samuel and others analyzed twenty-nine data management plans (DMP), specifically related to National Science Foundation grant proposals, to understand better, how faculty approach data management. The results help librarians build a foundation for future DMP services [2]. Coates and others examined five case studies that highlight common challenges for librarians to evaluate existing research data services in academic libraries, and suggested that evidence-based approach provides valuable information for assessing the still-emerging services [3].…”