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Research Data Management: Practical Strategies for Information Professionals

Edited by Joyce M. Ray
https://www.jstor.org/stable/j.ctt6wq34t
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    Research Data Management
    Book Description:

    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 maximize 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. This 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.

    eISBN: 978-1-61249-301-5
    Subjects: Library Science

Table of Contents

  1. Front Matter
    (pp. [i]-[iv])
  2. Table of Contents
    (pp. [v]-[viii])
  3. Introduction to Research Data Management
    (pp. 1-22)
    JOYCE M. RAY

    Interest in research data has grown substantially over the past decade. The reason for this is evident: the digital revolution has made it far easier to store, share, and reuse data. Scientific research data are now almost universally created and collected in digital form, often in staggering quantities, and all disciplines are making increasing use of digital data. Data sharing increases the return on the large investments being made in research and has the potential to exponentially advance human knowledge, promote economic development, and serve the public good, all while reducing costly data duplication.

    The Human Genome Project is a...

  4. PART 1: UNDERSTANDING THE POLICY CONTEXT
    • 1 The Policy and Institutional Framework
      (pp. 25-44)
      JAMES L. MULLINS

      This chapter is in two parts. In Part 1, the policy framework on the national level is addressed, including policies of funding agencies to the collective response of research libraries through the Association of Research Libraries (ARL) to position members to be actively engaged in data management planning and services. In Part 2, a general overview of the manner in which Purdue University Libraries responded is provided as a case study to demonstrate how administrative policy within a university and the positioning of one research library meet this changing environment.

      In 1999, John Taylor, director general of the United Kingdom’s...

    • 2 Data Governance: Where Technology and Policy Collide
      (pp. 45-60)
      MACKENZIE SMITH

      The Internet, web, and related technologies have created new opportunities to advance scientific research, in part by sharing research data sooner and more widely. The ability to locate, get access to, and reuse existing research data has the potential to both improve the reproducibility of research as well as enable new research. Because of this potential there is growing interest from across the research enterprise (researchers, universities, funders, societies, publishers, etc.) in data sharing and reuse in all research disciplines, but particularly in data-intensive disciplines where data is expensive to produce or is not reproducible. The long-term vision is of...

  5. PART 2: PLANNING FOR DATA MANAGEMENT
    • 3 The Use of Life Cycle Models in Developing and Supporting Data Services
      (pp. 63-86)
      JAKE CARLSON

      This chapter will introduce you to the concept and purpose of life cycle models as they apply toward developing and communicating data services in a library. Life cycle models are being adopted by agencies and organizations, such as DataONE (Strasser, Cook, Michener, & Budden, 2012), seeking to develop systems and promote sound practices around managing, organizing, and preserving research data. In the life sciences, life cycle models are used to depict the continuous sequence of stages that an organism will go through from birth to maturity, reproduction, and the renewal of the cycle, usually in a visual fashion. The premise behind...

    • 4 Data Management Assessment and Planning Tools
      (pp. 87-108)
      ANDREW SALLANS and SHERRY LAKE

      Data is one of the hottest topics in recent years. In the academic world, we see continuous discussion of new initiatives for data-intensive research, of how institutions and disciplines should engage with “big data,” and what new data skills are needed to remain competitive in a changing landscape. Much of this change is driven by advances in technology, leading to new opportunities for communicating, collaborating, and rethinking how research is done. Underneath it all, the fundamentals of managing research data become ever so much more important. Although the importance of managing research data is becoming better recognized in the academic...

    • 5 Trustworthy Data Repositories: The Value and Benefits of Auditing and Certification
      (pp. 109-126)
      BERNARD F. REILLY JR. and MARIE E. WALTZ

      Within the past decade the digital preservation community has come to embrace a primary set of criteria for assessing the capability of repositories to maintain digital content and information over time. Those criteria are embodied inTrustworthy Repositories Audit & Certification: Criteria and Checklist. Since 2007, the Center for Research Libraries (CRL) has used the criteria in audits of several digital repositories. The authors here reflect on the usefulness of the Trustworthy Repositories Audit and Certification (TRAC) criteria in light of the findings and outcomes of those audits.

      The authors also aim in this report to suggest the wider application of...

  6. PART 3: MANAGING PROJECT DATA
    • 6 Copyright, Open Data, and the Availability-Usability Gap: Challenges, Opportunities, and Approaches for Libraries
      (pp. 129-148)
      MELISSA LEVINE

      This chapter is about copyright as one of several significant bodies of law that touches on the creation, preservation, and use of data. And yet, this chapter barely discusses copyright at all, instead approaching copyright as a matter of policy, administration, and business choices that should minimize the complexity of copyright over the life cycle of research data. In doing so, the products of research may more easily be reused and reinvested.

      “Data is the new gold,” according to Neelie Kroes, vice president of the European Commission responsible for the Digital Agenda (Kroes, 2011). Computing power has increased exponentially at...

    • 7 Metadata Services
      (pp. 149-166)
      JENN RILEY

      The January 2011 introduction of a data management plan requirement in grant proposals made to the National Science Foundation (NSF) took the academic library world by storm. Many of these libraries quickly mobilized and partnered with sponsored research offices to provide assistance in meeting this requirement, and were prepared when subsequent United States federal granting agencies followed suit in their application procedures. The stakes were further raised in February 2013, when the U.S. White House Office of Science and Technology Policy (OSTP) issued a memorandum directing many federal funding agencies to develop plans for increasing public access to data generated...

    • 8 Data Citation: Principles and Practice
      (pp. 167-186)
      JAN BRASE, YVONNE SOCHA, SARAH CALLAGHAN, CHRISTINE L. BORGMAN, PAUL F. UHLIR and BONNIE CARROLL

      In the last decade, the amount of data created by large scientific facilities, sensors, new observation instruments, and supercomputing has outpaced our ability to process, store, and analyze the data. As technological factors—such as faster processors, better storage, and increased bandwidth—have enabled the much greater production and capture of data, the creation of standards to manage these data has not kept pace. Nor are data management issues solely limited to the data produced by high-performance computing (HPC) and scientific computing (SC); in fact, the aggregated data produced by individual researchers or small research groups may well dwarf that...

  7. PART 4: ARCHIVING AND MANAGING RESEARCH DATA IN REPOSITORIES
    • 9 Assimilating Digital Repositories Into the Active Research Process
      (pp. 189-202)
      TYLER WALTERS

      Digital repositories, including institutional repositories (IRs), are being integrated into emerging systems of e-research and associated virtual sites. These repositories are evolving to support large interdisciplinary research communities throughout the entire life cycle of the research process. Several factors are driving this development. Sponsored research, particularly in the science and engineering domains, is becoming increasingly multi-institutional. National research agendas, such as those funded by the National Science Foundation and the National Institutes of Health, often necessitate inter-institutional collaboration in the form of “Big Science” projects. Many of these projects are interdisciplinary in nature, involving scientists and humanists from many fields...

    • 10 Partnering to Curate and Archive Social Science Data
      (pp. 203-222)
      JARED LYLE, GEORGE ALTER and ANN GREEN

      Improvements in data processing and storage technology are resulting in an increase in research data on a variety of social, economic, and political subjects. Many datasets could be profitably reanalyzed, but they are at danger of being lost since they are never properly archived. Institutional repositories (IRs) are charged to preserve the scholarly products of their faculty or institution and are increasingly tapped to add data services, but not all feel prepared to curate and archive data. In some cases, IRs work closely with local experts who have a history of supporting data on their campuses (for example, data specialists...

    • 11 Managing and Archiving Research Data: Local Repository and Cloud-Based Practices
      (pp. 223-238)
      MICHELE KIMPTON and CAROL MINTON MORRIS

      When King Richard III of England died in the 1485 Battle of Bosworth Field (“Richard III of England,” n.d.), the words “research” and “data” were unknown. King Richard would not have believed that in 500 years his bones would be discovered under a parking lot, providing scholars with a wealth of information about his life and death (McRobbie, 2013). The world changed and we learned how to extract DNA from bone tissue using scientific methods that were unheard of when that long-ago “data” was preserved in a hasty grave (Jones, 2013). King Richard’s unheralded and unrecorded burial could be an...

    • 12 Chronopolis Repository Services
      (pp. 239-252)
      DAVID MINOR, BRIAN E. C. SCHOTTLAENDER and ARDYS KOZBIAL

      The National Science Foundation (NSF) requirement that researchers create a data management plan for each NSF proposal submitted after January 2011 reinforced to its constituency the need for long-term stewardship of data and research output. Other funding agencies already had other requirements in place (for example, the National Institutes of Health [NIH] data sharing requirement of 2003). These requirements make clear the importance of having infrastructure in place that enables the long-term preservation of digital objects.

      While researchers familiar with the language of the data life cycle might have had a solid enough understanding of phases comprising that life cycle...

  8. PART 5: MEASURING SUCCESS
    • 13 Evaluating a Complex Project: DataONE
      (pp. 255-274)
      SUZIE ALLARD

      Project evaluation is conducted to determine a project’s level of success as well as to help manage an ongoing project more efficiently. Using a systematic approach to evaluation allows for the identification of the project’s merit or significance (Scriven, 1999). Developing a systematic evaluation approach for a complex project in a data-intensive environment can be challenging. This chapter discusses the experience of creating and implementing an evaluation plan for the Data Observation Network for Earth (DataONE), an interdisciplinary, multi-institutional, multinational project that supports the data life cycle in the biological, ecological, and environmental sciences. DataONE is funded by the United...

    • 14 What to Measure? Toward Metrics for Research Data Management
      (pp. 275-300)
      ANGUS WHYTE, LAURA MOLLOY, NEIL BEAGRIE and JOHN HOUGHTON

      The importance of metrics for evaluating research data management (RDM) seems almost too obvious to state. Yet as the quotes below suggest, choosing metrics or indicators requires careful planning and consensus on what to measure and how. In RDM, that consensus has yet to be achieved. So while some of the metrics we refer to in this chapter employ readily countable things, such as downloads, most employ metrics that are not truly numeric, such as rating scales or categories of variables.¹

      “If you cannot measure something, your understanding of it is meagre.” Lord Kelvin

      “The most important things cannot be...

  9. PART 6: BRINGING IT ALL TOGETHER:: CASE STUDIES
    • 15 An Institutional Perspective on Data Curation Services: A View from Cornell University
      (pp. 303-324)
      GAIL STEINHART

      Interest in and support for cyberinfrastructure (CI) development and data-driven research has grown significantly in the past decade or so. Well-curated and accessible data are the feedstock for CI and data-driven research. As custodians of the scholarly record, research libraries might be presumed to have an important role as curators of research data. Libraries are not entirely new to supporting research data in other capacities, with roles such as geographic information systems and social science data librarians being fairly common.

      In spite of this seemingly natural fit, introducing and operating data services is a complicated undertaking. Publishing processes, models, and...

    • 16 Purdue University Research Repository: Collaborations in Data Management
      (pp. 325-346)
      D. SCOTT BRANDT

      A lot can be learned about research data by participating in research. It is one way librarians can learn about data life cycle and workflow needs of researchers. The Purdue University Libraries’ approach to data management evolved out of investigation of the needs for interdisciplinary research and the ability of librarians to partner and engage in it. The service includes data reference, consulting, planning, and collaboration. It is embedded in interactions across campus and in the Purdue University Research Repository (PURR). PURR is an institutional collaboration that provides help in data management planning, data publishing and discovery, and data preservation....

    • 17 Data Curation for the Humanities: Perspectives From Rice University
      (pp. 347-374)
      GENEVA HENRY

      At the start of the 21st century, it was uncommon to hear humanities scholars talk about their research in terms of data. By that time, however, some prominent efforts had emerged that allowed scholars to leverage computational resources to discover and present new information.¹ These new approaches would change earlier scholarly analyses and interpretations that were limited by the amount of information a human could manage, both cognitively and physically, with large volumes of printed text. Projects such as the Valley of the Shadow (Ayers, n.d.), the Perseus Digital Library (Crane, n.d.), and The Walt Whitman Archive (Folsom & Price, n.d.)...

    • 18 Developing Data Management Services for Researchers at the University of Oregon
      (pp. 375-392)
      BRIAN WESTRA

      The University of Oregon Libraries, like a growing number of academic libraries, employs a combination of strategies to develop and provide research data management support services. Efforts have included new or reconfigured faculty positions with responsibilities for research data management support; consultations and guidance on data management plans; training for graduate students and faculty in data management; a local institutional repository for preserving and sharing data; and finally, small pilot studies exploring research infrastructure collaborations targeted at data management needs early in the data life cycle. The result of this attention to the data curation needs of the campus is...

  10. CLOSING REFLECTIONS:: LOOKING AHEAD
    • 19 The Next Generation of Challenges in the Curation of Scholarly Data
      (pp. 395-408)
      CLIFFORD LYNCH

      Requirements for data curation are now well established across a wide range of scholarly disciplines, but particularly in the sciences and some social sciences, through a series of funder requirements for data management plans and policies mandating public access to large classes of research data. Institutional policies and journal editorial policies surrounding the management and availability of research data support and complement the funder-driven initiatives. The need for effective and affordable research data management services will only grow over the next decade.

      The previous chapters of this book have covered the evolution of the policy environment and discussed some of...

  11. About the Contributors
    (pp. 409-422)
  12. Index
    (pp. 423-436)
  13. Back Matter
    (pp. 437-437)