Recent years have seen a growing emphasis on the need for improved management of research data. Academic libraries have begun to articulate the conceptual foundations, roles, and responsibilities involved in data management planning and implementation. This paper provides an overview of the Engineering data support pilot at the University of Michigan Library as part of developing new data services and infrastructure. Through this pilot project, a team of librarians had an opportunity to identify areas where the library can play a role in assisting researchers with data management, and has put forth proposals for immediate steps that the library can take in this regard. The paper summarizes key findings from a faculty survey and discusses lessons learned from an analysis of data management plans from accepted NSF proposals. A key feature of this Engineering pilot project was to ensure that these study results will provide a foundation for librarians to educate and assist researchers with managing their data throughout the research lifecycle.
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.
is a CLIR/DLF Data Curation fellow, associate librarian, and a full-time researcher affiliated with the Clark Library for Maps, Government Information and Data Services. Since the summer of 2012, Natsuko has been involved in developing and implementing library data services. After joining the University of Michigan Library in 2009, the majority of her time and effort has been dedicated to textbook initiatives at the University of Michigan Library. Her research orientation and knowledge of both quantitative and qualitative methodological techniques has enabled her to conduct several textbook-related studies that examine and assess a wide range of potential roles the Library can play in increasing textbook affordability for the Michigan scholarly community. Natsuko most recently served as a project manager for the campus-wide eTextbook Initiative led by the University Library.
This video article provides an introduction to a data primer which leads data curators through the process of preparing a neuroimaging dataset for submission into a repository. A team of health sciences librarians and informationists created the primer which is focused on data from functional magnetic resonance images that are saved in either DICOM or NIfTI formats. The video walks through a flowchart discussing the process of preparing data sets to be deposited into a repository, key curatorial questions to ask for data that is highly sensitive, and how to suggest edits to this and other primers. The primer grew out of a data curation workshop hosted by the Data Curation Network.
Engineering researchers face increasing pressure to manage, share, and preserve their data, but these subjects are not typically a part of the curricula of engineering graduate programs. To address this situation, librarians at the University of Michigan, in partnership with the Climate and Space Sciences and Engineering Department, developed a new credit-bearing course to teach graduate students the knowledge and skills they need to respond to these pressures. The course was specifically designed to teach data management through the lens of climate and space sciences by incorporating relevant examples and readings. We describe the development, implementation, and assessment of this course and provide recommendations for others interested in building their own data management courses. [ABSTRACT FROM AUTHOR]
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