NSF Guide: Resources for Data Management Planning
This section provides some resources for addressing the NSF requirement for DMPs. It includes references to examples, data management tools, and data repositories. Please note: As data are unique, and tools for collection, storage, and analysis are technically evolving, the requirements for specific data sets will be, as NSF states, "determined by the community of interest and subject to the process of peer review and program management” within the NSF. NSF program directors are to act as consultants to help researchers best determine what constitutes an adequate data plan including giving data archive referrals.
Research Library Websites on Data Management Planning
ARL member libraries with structured comprehensive data management plans:
Resources about Developing DMPs
NSF Guidance on Specific Data Management Plans
Certain directorates within the NSF, however, provide explicit guidelines and advice on forming data management plans. As of November 2010 these directorates are the following:
Additional guidance may be found at “Data Management & Frequently Asked Questions (FAQs)” on the NSF website.
Data Curation, Digital Curation & Data Archive Resources (U.S. and International)
Data Repositories
Tools for DMPs and Assessing Research Data Needs
Authors: Patricia Hswe and Ann Holt
NSF Guide: Helping Researchers Create a Plan
As required by the NSF, the DMP is a supplementary document, intended to describe how the proposed project will adhere to the agency’s policy for disseminating and sharing research results. Researchers preparing grant applications in response to NSF solicitations will need support from librarians, such as subject specialists and data curators/archivists, as well as from information technologists, to address data management planning.
Researchers may not look, at least initially, to their academic libraries for assistance. The NSF requirement thus represents a new opportunity for collaboration between librarians and researchers, one in which – to get started – it may be incumbent on librarians to reach out to research communities, as well as to the administrative unit on campus responsible for oversight of grant-funded research, in order to work together on general guidelines for constructing a plan for managing research data.
How Does the NSF Requirement Fit in with the Grant-Writing Process?
A DMP grows out of understanding how data should be collected, normalized, processed, analyzed, preserved, used, and re-used over their lifetime. The lifecycle management of data is often referred to as data curation. (Digital curation more typically denotes lifecycle management of digital objects, whether these are data or other types of content.)
With the new NSF requirement, the grant-writing process offers a chance for researchers and librarians to plan together for curation of research data before the data have been generated and, therefore, to think carefully about data and metadata standards and policies for access and use, for example. Librarians could consider an initial session with researchers to learn about their data as a “data interview,” not unlike a “reference interview.” In this regard, an article such as“A Subject Librarian’s Guide to Collaborating on e-Science Projects” (Garritano & Carlson, 2009) suggests questions that librarians can ask researchers at the outset about their data:
- What kinds of data will be collected or created – formats, type, extent?
- Besides the researcher(s) on the project, who else should be given access to the data?
- Who owns the data?
- Will there be restrictions on the data?
- How might the data be used, reused, and repurposed?
In asking questions like the above, the construction of a data management plan can be instrumental for librarians involved in collection development and management activities—it can be viewed as a prelude to future collection and stewardship of data sets. “In the end, a librarian can help researchers build their collections of data in order to make it as useful as possible to current and future researchers who may be interested in the same or similar research.” (Garritano & Carlson, 2009)
There are tools available to enable librarians to assess researchers’ data management needs, among them:
In addition, Purdue University—in collaboration with the University of Illinois at Urbana-Champaign—has developed a Data Curation Profiles Toolkit (project description).
How Are Libraries Communicating about this with Researchers?
For the most part, libraries are communicating about the NSF’s change to the implementation of its data sharing policy via their websites. Our Resources for Data Management Planning page lists a selection of web pages developed at, or involving, research libraries, mostly in response to the NSF call.
Liaison librarians also have important roles to play in communicating with researchers to help them meet the NSF requirement. At Purdue University Libraries liaison librarians are receiving training in the use of the Data Curation Profile tool; the tool has been adapted for ascertaining particular areas of attention for sharing, distributing, and managing research results in accordance with the NSF’s Grant Proposal Guide. At the University of Wisconsin-Madison (UW-M) Libraries, liaison librarians and the campus-IT strategic-planning task force are working together to plan research data management consulting services. In addition, the liaisons at UW-M Libraries have been invited to participate in a joint library/IT mailing list focused mainly on e-research topics; the mailing list will also be applied for “crowdsourcing” responses to the NSF data sharing policy.
Data Management Planning is a Collaborative Effort
Addressing the DMP requirement from the NSF means bridging the space between librarians, researchers, and their data. A coherent plan will necessitate collaboration across units within and beyond the research library. Many ARL member libraries, such as those listed above, are intently engaged in collaborative efforts. One example is Cornell University Library, which has representation in the recently formed Research Data Management Services Group (RDMSG). The planning group for the RDMSG consisted of faculty, staff, and librarians from a range of disciplines, including the social sciences and astronomy, and range of interdisciplinary groups and centers, such as the DISCOVER Research Services Group and the Center for Academic Computing. The RDMSG reported on its investigation into creating new services for research data management planning, determining existing capacities and analyzing gaps to overcome, which could prove a useful model for other libraries going forward in their own exploration of new service development.
Authors: Patricia Hswe and Ann Holt
NSF Guide: A New Leadership Role for Libraries
Academic libraries are well poised to help researchers meet the new NSF requirement, which also presents an array of promising opportunities for leadership in this realm:
- Liaison librarians are familiar with the research data needs of their faculty. Many subject specialists in biology, engineering, geosciences, the social and behavioral sciences, economics, and other areas covered by programs and directorates in the NSF already work closely with faculty and know the challenges of managing and sharing research data.
- This is next-generation librarianship. The curation of research data is an activity that has gained traction in the wake of library and information science programs offering concentrations in data curation and institutes in digital curation, promising a cohort of librarians qualified to meet the challenges of managing data.
- Collaboration is reinforced as a significant way of building capacity. Data management planning demands cross-departmental, even cross-campus, communication and collaboration, and for many research libraries such inreach/outreach efforts are well established. For others, the change in the NSF policy opens up new opportunities for collaboration and thus new ways of modeling that process.
- This is a paradigm shift for libraries and librarians on many levels. The NSF requirement points up new opportunities for libraries, such as the impetus for creating services relevant to the management of research data, and for librarians, such as in the area of collection development (e.g., since data sets will increase in importance, how does this affect collection management and development policies?) and in the acquiring of new skill sets.
- It’s not about just content anymore. Data management plans resulting from this requirement have great potential to inform how libraries should curate research data in a programmatic, standardized way for continuing access and re-use.
Authors: Patricia Hswe and Ann Holt
Unpacking the NSF Requirement
On May 10, 2010, the National Science Foundation (NSF) disclosed a new development in its data sharing policy: the agency announced that, by fall 2010, it intended to require data management plans (DMPs) as part of all proposals responding to NSF grant funding solicitations. Chapter II of the current Grant Proposal Guide (NSF 11-1 January 2011), under “Special Information and Supplementary Documentation,” provides some detail on what a data management plan should encompass.
The Context: Providing Access to Federally Funded Research Data
Like many federal agencies that provide research funding, the NSF has had a data sharing policy in place for many years, in compliance with the Office of Management and Budget’s (OMB) Circular A-110. Approved in 1999 and enacted the following year, the OMB’s Circular A-110 requires that data generated from federally funded research be made publicly available via the process instituted by the Freedom of Information Act. A more recent development is the 2009 Open Government Initiative, charging federal agencies to take a committed stance toward effecting transparency, participation, and collaboration in their activities.
For many years the NSF has long expected investigators to publish, with proper authorship attribution, significant research findings and to share – within an acceptable period of time and at moderate expense – data sets, samples, collections, and other research-related materials generated by funded projects. In the last five years the agency has made further inroads in this area. For example, its solicitation for the Sustainable Data Preservation Access and Network Partners (DataNet), launched in 2007, marks a continuing effort to address the challenges of keeping digital data accessible, usable, and reusable.
The Gist of the New Requirement
As the NSF states in its current Grant Proposal Guide, data management plans are intended to document how research data will be described, accessed, archived, shared, re-used, and re-distributed over the length of the funded project and beyond. The guidance provided by the NSF is general in nature, since specifics for the plan will depend on what the agency refers to as the “community of interest”—essentially the domain or discipline to which the project proposal is relevant. Not to exceed two pages, data management plans are to be part of the supplementary materials in NSF grant proposals. Basic components to such a plan might be as follows:
- Types of data, samples, physical collections, software, curriculum materials, and other materials that are generated for the duration of the project
- Standards for data and metadata format and content
- Access and sharing policies, with stipulations, as needed, for privacy, confidentiality, security, intellectual property, or other rights or requirements
- Policies for re-use, re-distribution, and creation of derivatives
- Plans for archiving data, samples, and other research outcomes, as well as for maintaining their access
The list above represents a suggestion. A DMP may include all of the above, or some of it.
The NSF also notes that a DMP may consist of a statement that no plan is necessary, as long as “clear justification” for such an omission supports the statement.
Certain directorates within the NSF, however, provide explicit guidelines and advice on forming DMPs. See our Resources on Data Management Planning.
Additional guidance may be found at “Data Management & Frequently Asked Questions (FAQs)” on the NSF website.
Why the Change to NSF’s Policy?
With the May 2010 announcement, the NSF essentially modified its policy implementation for data sharing. Various factors informed this decision, including the increasingly data-centric, collaborative nature of science research and, by extension, the need for more openness and communication about research findings. It also signals an explicit recognition of the realities of research in the “Digital Age.” As assistant director for the NSF’s Computer & Information Science & Engineering directorate, Jeannette Wing, stated in the May 2010 press release, “Digital data are both the products of research and the foundation for new scientific insights and discoveries that drive innovation.” Most important, the agency’s new requirement bespeaks its design for a more encompassing, programmatic take on data sharing and data curation.
Authors: Patricia Hswe and Ann Holt
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