Case Studies on Research Data Management in Libraries

LIBER (Association of European Research Libraries) ’s Steering Committee on Scholarly Communication and Research Infrastructures has collected case studies, hosted by or with strong involvement of libraries in research data management. These studies describe policies and strategies that pave the way for the creation, institutional integration and the running of support services and underlying infrastructures. In addition, challenges and lessons learned are described, and ways-forward outlined.

The 11 case studies can be accessed here.


Data Management for Undergraduate Researchers

Two data service specialists from Purdue University Libraries have recently published a research guide (LibGuide) to help undergraduate students with data management. This LibGuide has several different tags: data management plans, file naming conventions, documentation, security/backup, and publication/preservation.

While a number of  research guides were published on the subject of data management across institutions, there are not that many LibGuides that particularly focus on undergraduate researchers. This may be of great use to other  librarians for creating a similar data management guide for undergraduate researchers.

Take a look at the LibGuide: Data Management for Undergraduate Researchers

Research Data Needs Assessment Study by the University of Iowa

The data management report, authored by Shawn Averkamp, Xiaomei Gu, and Ben Rogers, presents survey and interview findings from their recent data needs assessment study. This report was commissioned by the University of Iowa Libraries with the intention of performing a survey of the campus landscape and identifying gaps in data management services. The first stage of data collection consisted of a survey conducted during summer 2012 to which 784 responses were received. The second phase of data collection consisted of approximately 40 in-depth interviews with individuals from the campus and were completed during summer 2013. Findings are presented within five broad areas of data management: 1) data management planning, 2) data storage, 3) data organization and analysis, 4) data publishing and dissemination and, 5) sensitive data and compliance, with additional findings reported in the areas of research culture and funding models.

Blog: Building and Visualizing the Research Lifecycle Model

Followers of Data Forwards will be interested in reading a recent blog post by Fe Sferdean at Data@MLibrary. She wrote about the University of Michigan Library’s data initiative by focusing on the role of Research Lifecycle Committee and its work progress.

Fe notes in her blog, “(o)ne main focus of the committee was creating a generic research lifecycle model as a visual tool to communicate the research process and the library services to the U-M campus. Illustrating the research and data lifecycles helped the committee to analyze and discuss the definitions and overall layout of the different stages of research and how the data lifecycle is a part of the research process.”

Continue reading Fe’s blog post….

Research Data Management: Principles, Practices, and Prospects | CLIR

CLIR Publishes a new report on Research Data Management: Principles, Practices, and Prospects

This report examines how research institutions are responding to data management requirements of the National Science Foundation, National Institutes of Health, and other federal agencies. It also considers what role, if any, academic libraries and the library and information science profession should have in supporting researchers’ data management needs.

The report (in PDF) is available from: