Research Data Management

It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximise the return on investment of public funds.

To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of information professionals who are already involved in the acquisition, management, and preservation of data in their daily jobs. Data services include planning and implementing good data management practices, thereby increasing researchers’ ability to compete for grant funding and ensuring that data collections with continuing value are preserved for reuse.

volume provides a framework to guide information professionals in academic libraries, presses, and data centers through the process of managing research data from the planning stages through the life of a grant project and beyond. It illustrates principles of good practice with use-case examples and illuminates promising data service models through case studies of innovative, successful projects and collaborations.

Contributors include: James L. Mullins, Purdue University; MacKenzie Smith, University of California at Davis; Sherry Lake, University of Virginia; Bernard Reilly, Center for Research Libraries; Jacob Carlson, Purdue University; Melissa Levine, University of Michigan; Jenn Riley, University of North Carolina at Chapel Hill; Jan Brase, German National Library of Science and Technology; Seamus Ross, University of Toronto; Michele Kimpton, DuraSpace; Brian Schottlaender, University of California, San Diego; Suzie Allard, University of Tennessee; Angus Whyte, Digital Curation Centre; Scott Brandt, Purdue University; Brian Westra, University of Oregon; Geneva Henry, Rice University; Gail Steinhart, Cornell University; and Cliff Lynch, Coalition for Networked Information.