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NSF Data Management Plan

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Presentation on theme: "NSF Data Management Plan"— Presentation transcript:

1 NSF Data Management Plan
Steve Riesbeck Research Grants Development Coordinator Russ College of Engineering and Technology Stocker 182 3-0631

2 NSF Data Management Plan
NSF Guidelines Definitions Contents of your plan

3 NSF Guidelines: PAPPG “Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing.” ---NSF Proposal and Award Policies and Procedures Guide, Section VI.D.4.b.

4 NSF Guidelines: ENG The full policy specifically requires prompt preparation and submission of publications, recognizes allowances for restricting release of privileged or proprietary information, encourages sharing of software and inventions, and recognizes intellectual property rights. Such dissemination of data is necessary for the community to stimulate new advances as quickly as possible and to allow prompt evaluation of the results by the scientific community. ---NSF Engineering Directorate guidelines

5 NSF Guidelines: Solicitation
Example: Program Solicitation NSF Nanotechnology Undergraduate Education (NUE) in Engineering Data Management Plan: The PAPPG contains a clarification of NSF's long standing data policy. All proposals must describe plans for data management and sharing of the products of research, or assert the absence of the need for such plans. FastLane will not permit submission of a proposal that is missing a Data Management Plan. The Data Management Plan will be reviewed as part of the intellectual merit or broader impacts of the proposal, or both, as appropriate. Links to data management requirements and plans relevant to specific Directorates, Offices, Divisions, Programs, or other NSF units are available on the NSF website at: See Chapter II.C.2.j of the GPG for further information about the implementation of this requirement.

6 NSF Data Management Plan
What data are included? Research data are formally defined as “the recorded factual material commonly accepted in the scientific community as necessary to validate research findings” by the U.S. Office of Management and Budget (1999). The basic level of digital data to be archived and made available includes (1) analyzed data and (2) the metadata that define how these data were generated. These are data that are or that should be published in theses, dissertations, refereed journal articles, supplemental data attachments for manuscripts, books and book chapters, and other print or electronic publication formats. • Analyzed data are (but are not restricted to) digital information that would be published, including digital images, published tables, and tables of the numbers used for making published graphs. • Necessary metadata are (but are not restricted to) descriptions or suitable citations of experiments, apparatuses, raw materials, computational codes, and computer-calculation input conditions. ---NSF Engineering Directorate Guidelines

7 NSF Data Management Plan
What data are not included at the basic level? The Office of Management and Budget statement (1999) specifies that this definition does not include “preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues.” Raw data fall into this category as “preliminary analyses.” ---NSF Engineering Directorate Guidelines

8 NSF Data Management Plan
Exceptions Some proposals may involve proprietary or other restricted data. For example, projects having proprietary information that will eventually lead to commercialization, such as Engineering Research Center (ERC), Nanoscale Science and Technology Center (NSEC), Industry/University Cooperative Research Center (I/UCRC), Small Business Innovative Research (SBIR), Small Business Technology Transfer (STTR), and Grant Opportunities for Academic Liaison with Industry (GOALI) awards. In addition, membership agreements, contracts, involvement with other agencies, and similar obligations may place some restrictions on data sharing. Any such data-management issues should be discussed as well as the conditions that might prevent or delay the sharing of data. The proposal’s DMP would address the distinction between released and restricted data and how they would be managed. Exceptions to the basic data-management policy should be discussed with the cognizant program officer before submission of such proposals. A similar situation arises from the special circumstances that arise from requirements to protect human subjects. Data-sharing policies for awards that involve human subjects should recognize and address human-subjects protocols and the need to protect privacy and confidentiality (see .

9 Your Data Management Plan
Contents Expected data Period of data retention and data sharing Data formats and dissemination Data storage and preservation of access Post award monitoring NSF Page Limit = 2 pages NOTE: More stringent data management requirements may be specified in particular NSF solicitations (Template available)

10 Your Data Management Plan
EXPECTED DATA In the performance of the proposed project, the following types of data, samples, physical collections, software, curriculum materials, and other materials are expected to be produced: <<List or describe what primary data is expected to be produced>> From these, the following types of data are to be retained: <<List or describe what will be retained>> Data for retention and sharing does not include preliminary analyses (to include raw data), drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues.

11 Your Data Management Plan
PERIOD OF DATA RETENTION AND DATA SHARING Established policies for project data retention and data sharing and best practices at Ohio University shall apply. Retention of research data shall be three years after conclusion of the award or three years after public release, whichever is later. Public release of data shall be at the earliest reasonable time; namely, the earliest reasonable time is immediately after timely publication. Exceptions requiring longer retention periods may occur when: 1) data supports patents; 2) questions arise from inquiries or investigations with respect to research; 3) student involvement requires data to be retained for a timely period after a degree is awarded; 4) data represents a significantly large collection that is widely useful to the research community; 5) data is identified as proprietary or restricted. Research data that support patents shall be retained for the entire term of the patent. For the proposed project, the following exceptions are anticipated: <<List or describe any anticipated exceptions plus the rationale for why data requires longer retention or limitation on public release>>

12 Your Data Management Plan
PERIOD OF DATA RETENTION AND DATA SHARING (cntd) In order to make data available to others, including metadata, the following specific data formats, media, and dissemination approaches shall be used: <<List or describe applicable formats/media, and how the data will be shared and disseminated>> Established policies and best practices at Ohio University for public access and sharing shall apply, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. A listing is available online at and

13 Your Data Management Plan
DATA STORAGE AND PRESERVATION OF ACCESS The following physical and cyber resources and facilities shall be used for the effective preservation and storage of research data: <<List or describe the resources and facilities to be used for storage and preservation>> The lead PI shall be responsible for assuring data storage and access, to include project performance and compliance of collaborators and sub-awardees.

14 Your Data Management Plan
POST-AWARD MONITORING After an award is made, data management will be reported to NSF primarily through the normal Annual and Final Report process and through evaluation of subsequent proposals. Data management shall be reported in subsequent proposals by the PI and Co-PIs under Results of prior NSF support.

15 Research Grants Development Coordinator
Steve Riesbeck Research Grants Development Coordinator Russ College of Engineering and Technology Stocker 182 3-0631 15

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