Per the NIH Genomic Data Sharing Policy published in 2014, researchers submitting proposals for projects that will generate large-scale human or non-human genomic data must include a genomic data sharing plan. Regarding which of the sections below are recommended or mandatory, the following guidance is provided by the NIH:
[A]ll applicants proposing to generate human or non-human data, elements 1 and 2, a description of the data type and the data repository, should be provided at the time of the application. Applicants proposing to generate human data should also provide information addressing elements 3-5 (data submission and release timeline, IRB assurance of the genomic data sharing plan, and appropriate use of the data, respectively) and, if applicable, element 6 (request for an exemption to the submission) prior to award. Applicants proposing to generate non-human data need also to address element 3 (data submission and release timeline) prior to award.
The grant proposal guidlines for projects funded by the Sloan Foundation are available from http://www.sloan.org/apply-for-grants/grant-proposals/, and may vary depending on the type of project and amount of funds requested.
Each set of guidelines, however, requires the submission of an Information Products Appendix which specifically includes research data and requires PIs to address the following:
Per the DoD Public Access Plan released in February, 2015, supplementary data management plans are integral to all contract or grant proposal packages. The supplement will describe how data management will adhere to DoD policy on the dissemination and sharing of research products. Note that the DoD's Public Access plan specifically references a Department implemented data management and discovery network, which utilizes a common core metadata schema. Links are provided below.
In broad terms, the DMP will describe:
From the DoD Public Access Plan: http://www.dtic.mil/dtic/pdf/dod_public_access_plan_feb2015.pdf
From the Institute of Education Sciences (IES) Policy Statement on Data Sharing in IES Research Centers:
Data sharing provides opportunities for other researchers to review, confirm or challenge study findings, which is an important aspect of the scientific process. In addition, data sharing can enhance scientific inquiry through a variety of other analytic activities, including the use of shared data to: test alternative theories or hypotheses; explore different sets of research questions than those targeted by the original researchers; combine data from multiple sources to provide potential new insights and areas of inquiry; and/or conduct methodological studies to advance education research methods and statistical analyses.
Provide a description of the data to be collected or used. Explain what the contents of each dataset will be, including if known the number and types of files as well as file sizes. Additionally, information about data collection and quality assurance methods should be included here. Consider the following questions:
Per the IES, data sharing may not compromise the rights and privacy of human subjects. Because investigators will be expected to share data, consideration should be given to study design and procedures which will facilitate access while protecting the rights of participants and confidentiality of the data. In particular, data use and sharing information should be provided as part of the informed consent process, while data to be shared should be free of identifiers that would allow direct or deductive disclosure of study participants.
Refer to applicable IRB protocols, and consider the following:
Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data. Consider these questions:
Per the IES:
Timely data sharing is important to the scientific process. IES thus expects that data will be shared no later than when the main findings from the final study dataset are published in a peer-reviewed scholarly publication.
The IES acknowledges that there may be issues associated with providing access to data when the data collected are proprietary (e.g., when a published curriculum is being evaluated). Any restrictions on data sharing, such as a delay of disclosing proprietary data, should be presented in the DMP.
Describe the format of your data, and think about what details (metadata) someone else would need to be able to use these files. Describe the structural standards that you will apply in making data and metadata available.
The template provided by online DMPTool offers the following guidance:
IES acknowledges that there are several methods to share data. These include the investigator taking on the responsibility for data sharing, which may involve making data available to the requestor through a variety of means, including their institutional or personal website Use of a data archive or data enclave. Archives can be particularly attractive for investigators concerned about a large volume of requests, vetting requests, or providing technical assistance for users seeking help with analyses. Researchers can use a data archive or enclave when datasets cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing, or use agreements that prohibit redistribution. Use of some combination of these methods. A mixed method for data sharing (is allowed) that allows for more than one version of the dataset and provides different levels of access depending on the version. Consider the following: Will you share data via a repository, handle requests directly or use another mechanism?If your method of sharing is with an archive, which archive/repository/database have you identified as a place to deposit data?What procedures does your intended long-term data storage facility have in place for preservation and backup?What is the long-term strategy for maintaining, curating and archiving the data?What metadata/documentation will be submitted alongside the data or created on deposit/ transformation in order to make the data reusable?What related information will be deposited?What costs if any will your selected sharing method charge (In the budget and budget justification sections of the application, include and describe the costs of data sharing)?
Generally, describe your long term plans for storing your data and making it available. You should include information about:
Specifically, the IES requires researchers to specify whether or not interested parties will be subject to the conditions of a formal data sharing agreement. Keeping in mind the need to balance sharing requiremetns with legal and ethical duties to protect the privacy of study participants as noted above, consider the following:
Describe any circumstances that prevent data sharing, including statutory confideniality requirements (HIPAA, FERPA, etc.).
Per the Department of Energy's Statment on Digital Data Management, proposals submitted after October 1, 2014 will be required to include a Data Management Plan. The DOE's suggested elements of a data management plan with links to resources are provided below.
NOTE: At the request of DOT lawyers, the DMP template provided by the online DMPTool is accompanied by the following disclaimer:
“This tool serves to provide guidance for how to prepare a Data Management Plan (DMP). The output of this tool does not constitute an approved government form. Those preparing DMPs for submission to the U.S. Department of Transportation (USDOT) should use their best judgment in determining what information to include. USDOT has identified five (5) broad areas that should be addressed in a DMP, but is not requiring any specific information to be included in any submitted DMP. USDOT may, at its discretion, establish an Office of Management and Budget-approved information collection. Once approved, the information collection will become a form with a control number, and certain DMP elements may become mandatory.”
With those caveats in mind, researchers are encouraged to refer to the detailed template provided by the online DMPTool.
The recommended sections and guiding questions provided in the linked template below are taken from the foundation website's DMP guide. Each question may not apply to a given project, but researchers should answer as completely as possible those which are relevant.
The Institute of Museum and Library Services (IMLS) requires a DMP for projects that develop digital content. The requirement includes specific recommendations and questions depending on whether a project involves the creation of digital datasets, software tools or electronic systems, and/or collections or databases of new content or metadata. All researchers are required to complete the section covering Copyright and Intellectual Property Rights, along with whichever other additional sections apply.
The Digital Stewardship Supplementary Information and the Digital Product forms below include more information. Please contact Research Data Services with any questions about addressing the requirements.
The Joint Fire Science Program requires submission of a maximum two page DMP with all proposals. From the JFSP application requirements:
It is the intent of the Joint Fire Science Program (JFSP) that all data collected or generated through JFSP funds be of high quality and be made freely available to others within a reasonable time period.
NASA's Data Management Plan requirements are described in the administration's 2014 Public Access Plan. With limited exceptions including human subjects research, proprietary data, and sensitive or export controlled data, the requirements apply to all NASA employees and recipients of NASA research funds. Requirements as broadly described on the NASA-Funded Research Results webpage include:
The online DMPTool provides a template with additional guidance.
Similar to the NSF, the NEH Office of Digital Humanities requires a short DMP, not to exceed two pages, to be submitted as a supplementary document. Current documentation, accessible from the links provided below, notes that DMPs are considered during the peer review of proposals, and that post award reports are expected to include discussion of compliance with the plan.
Since 2014, the NIJ has required funding applicants to submit a 1-2 page Data Archiving Plan with all proposals. In the plan, researchers are asked to demonstrate their recognition that data sets resulting from NIJ funded research must be submitted for archiving (typically to the National Archive of Criminal Justice Data) and to describe how the data will be curated or managed to facilitate replication of results. Per the NIJ's Data Archiving Plans for NIJ Funding Applicant website, the plan must briefly describe:
More information is available on the website. A Data Archiving Plan template is also available from the online DMP Tool.
From NOAA's Data Management Procedural Directive:
NOAA Administrative Order (NAO) 212‐15, Management of Environmental Data and Information, states that environmental data is to be managed based upon a lifecycle that includes developing and following a data management plan...The goal of the Data Management plan is to ensure that data are properly collected, documented, made accessible, and preserved for future use in a NOAA Data Center or other longterm archive facility.
Key concepts as defined in the Data Management Plan for NIFA-Funded Research Projects documentation released April, 2015:
Essentail elements of a USDA NIFA Data Management Plan are described in the sections below.
The United States Geological Survey provides comprehensive data management planning guidance covering the full spectrum of the research data lifecycle. Accordingly, data management plans which fully address the concepts and issues defined by the USGS will be more comprehensive than the two-page, high level overviews requested by other agencies and sponsors. More detailed information and sample plans are available from USGS Data Management.
The USGS DMP template generally follows the USGS Science Data Lifecycle Model, a high level view of how data relates to project workflows from data planning to preservation and publishing. This template is not prescriptive but meant as guidance for individuals and Centers/Programs who want to create their own Data Management Plans.
Consider these topics and questions describing very basic information about the project and the appropriate contacts:
Plan and Acquire elements of the USGS Science Data Lifecycle: Plan refers to planning considerations before the handling of the project's data assets. Acquire describes the activities related to new or existing data that are collected or generated.
Consider these topics and questions:
Describe and Manage Quality elements of the USGS Science Data Lifecycle: Describe emphasizes documentation of every stage of the lifecycle to ensure the data assets and methods can be understood, evaluated for validity, and potentially reused. Manage Quality includes considerations for quality assurance and quality control (QA/QC) measures.
Consider these topics and questions:
Backup/Secure and Preserve elements of the USGS Science Data Lifecycle: Backup/Secure involves managing risks and accessibility to the data throughout the lifecycle. Preserve highlights important activities that should be taken to ensure long-term preservation of data, metadata, ancillary products, and additional documentation.
Consider these topics and questions:
Publish and Share elements of the USGS Science Data Lifecycle: Publish and Share highlight important considerations related to traditional peer-reviewed publications and dissemination of the data through Web sites, data catalogs, social media and other outlets.
Consider these topics and questions:
A good resource for developing any data management plan is the DMP Tool Online.
By selecting University of New Mexico from the drop down list on the sign in page, you will be able to access templates created by our Data Librarians, as well links to UNM specific recommendations and resources.