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The Research Administration Management Systems & eSubmission (RAMSeS) system has been updated to include a Data Management and Sharing section in the RAMSeS Internal Processing Form (IPF). The Data Management and Sharing section will appear only for proposals for projects categorized as research. The Office of Sponsored Programs (OSP) has identified the following as falling under this category: Organized Research (OR), Clinical Trials (CT), and Phase 4 Clinical Trials (C4). Questions about the applicability of data management and sharing plan (DMSP) requirements to your proposal should be directed to

The purpose of the Data Management and Sharing section in the IPF is to support compliance with funding agency policies for research data management and sharing. It is important that information provided in the form is complete and accurate to ensure that campus resources are available to support data management and sharing activities as described in the Data Management and Sharing Plan (DMSP) and that the project budget includes sufficient resources to cover the cost of necessary tools and services for data management and sharing.

The information below provides guidance for each question in the Data Management and Sharing section in the RAMSes IPF.

Have you submitted a Data Management and Sharing Plan to the Research Data Management Core (RDMC) for review?

Every DMSP submitted via RAMSeS as part of a proposal package is subject to audit by the RDMC audit team. If the audit determines that the DMSP does not meet policy requirements for content and/or cannot be feasibly implemented given available resources and/or the proposed budget, the investigator will be prompted to revise and resubmit the DMSP. This may delay submission of the proposal to the funding agency. 

To avoid proposal submission delays, investigators are strongly encouraged to use the DMPTool to write their DMSP, and to take advantage of the RDMC’s DMSP review service, which includes a comprehensive inspection of the DMSP for completeness, appropriateness, and compliance prior to proposal submission. RDMC asks that you submit your request for DMSP review well in advance of the funding agency’s proposal due date to ensure that reviewers have sufficient time to conduct a comprehensive review and for revision and resubmission if necessary. While not a requirement, RDMC review of the DMSP draft ideally should be considered a key part of the proposal writing and assembly (i.e., pre-award) process.  

Writing a Data Management and Sharing Plan
Data Management and Sharing Plan Review

Will managing and sharing project data require dedicated personnel, specialized equipment, and/or other additional services? 

The proposal budget and budget justification should include allowable costs for data management and sharing. These costs may include data curation, file processing, de-identification, infrastructure for local data management and preservation, and repository fees. Review funder policy and guidance documents to determine which costs are considered allowable by the funding agency. 

Note that budgets that do not include sufficient funds to cover the cost of data management will be subject to modification if and when the grant is awarded. Therefore, it is important that the proposed budget accurately reflects the estimated costs of managing and sharing the data specific to the proposed project.

Budgeting for Research Data Management and Sharing
UNC OSP Policy: Proposal Budget Requirements
NIH: Budgeting for Data Management and Sharing
NIH Policy Supplement: Allowable Costs for Data Management and Sharing

Will your data include any of the following? 

The data generated by the project may have certain characteristics that require special considerations for data management and sharing. These considerations should be reflected in both the DMSP and, in some cases, the data management and sharing budget and budget justification.

Personally identifiable information (PII) or protected health information (PHI) 

Investigators must always comply with applicable laws, regulations, guidance, and policies related to human subjects research and the protection of participant privacy. The DMSP should describe specific provisions for protecting the privacy, rights, and confidentiality of study participants.  

Note that investigators should not assume that data derived from human participants are exempt from data management and sharing policies. Whenever feasible and legally acceptable, investigators should consider ways to share sensitive data such as through informed consent language, de-identification, certificates of confidentiality, access controls, limitations on data reuse, and/or other protective measures.  

Some of these provisions for sharing sensitive data may have implications for the project budget when they require additional personnel, resources and/or tools. Costs for data de-identification and access control management, for example, can be significant depending on personnel and infrastructure needs for implementing these measures. These costs should be included in the budget and described in the budget justification. 

If, after considering available options, sharing project data derived from human participants is determined to not be feasible, the DMSP should include a compelling explanation as to why the data cannot be shared despite available strategies for sharing sensitive data. 

UNC Office of Human Research Ethics
NIH Principles and Best Practices for Protecting Participant Privacy
NIH Policy Supplement: Protecting Privacy When Sharing Human Research Participant Data

American Indian/Alaska Native participant data 

There is a growing awareness that the recent emphasis on data management and sharing has not considered the rights and interests of American Indian/Alaska Native Tribes, who are rightfully asserting greater control and oversight over the use of Indigenous data and Indigenous Knowledge.  

Some funding agencies have issued additional guidance on the responsible stewardship of Indigenous data and Indigenous Knowledge to promote an understanding and respect for Tribal sovereignty and to advance best practices for mitigating further harms while also maximizing benefits to Indigenous Peoples.  

Investigators proposing projects that produce or use American Indian/Alaska Native participant data should review funding agency-issued guidance and resources on best practices for managing and sharing Indigenous data and Indigenous Knowledge and consider ways to incorporate these best practices into the DMSP. 

CARE Principles for Indigenous Data Governance
NIH Considerations for Researchers Working with AI/AN Communities

NIH Policy Supplement: Responsible Management and Sharing of American Indian/Alaska Native Participant Data

Proprietary/copyrighted data

While funding agencies expect that investigators maximize appropriate and feasible sharing of project data, the use of existing data obtained from third-party sources may introduce limitations on data sharing. Some data providers consider their data to be proprietary and therefore prohibit or impose restrictions on data reuse and redistribution. Investigators are expected to comply with data use agreements, licenses, and/or applicable copyright laws that limit or prohibit data sharing. In these cases, the DMSP should describe such restrictions in detail as part of a compelling reason for limiting or refusing data sharing. 

Resources coming soon

Genomic data 

Some sponsors have issued additional data management and sharing policies that include additional expectations for projects that generate genomic data. Investigators proposing projects that produce and/or use human or non-human genomic data should review these policies carefully to fulfill all requirements of the proposal package. 

For NIH, these expectations are outlined in the Genomic Data Sharing policy, which requires that a plan for sharing genomic data be incorporated into sections of the DMSP (rather than in a separate genomic data sharing plan, which was a requirement under previous policies). Information about the genomic data type; the repository to be used for submitting genomic data; informed consent, Institutional Certifications, data sharing limitation; and genomic summary results should be included in the DMSP. 

NIH Genomic Data Sharing Policy

Large-volume data (>2TB)

Projects that produce very large volumes of data should expect to commit a significant portion of their budget to archival preservation.  Budgeted amounts should include the cost of not only long-term storage, but also the cost of transferring data in and out of storage. 

Resources coming soon

Any other data that present ethical, legal, or technical issues that may limit your ability to share the data

While there are very few reasons that data cannot be shared, there may exist other circumstances in which this may be the case. The DMSP should describe situations that may limit or preclude the ability to share project data as part of a compelling rationale for limiting sharing.

NIH FAQs: What are justifiable reasons for limiting sharing of data?

Enter the name(s) of the repository(ies) selected for preserving and sharing project data.

Data generated or used by the research project should be shared in an established repository that offers tools and services for long-term data preservation and access. Some sponsors may define characteristics of an appropriate repository or specify certain repositories for data deposit and sharing. Investigators should review the notice of funding opportunity/program solicitation carefully for specific data repository requirements. 

If the funding agency does not require data deposit in a specified repository, investigators have many repositories to choose from. Which repository is best suited for the long-term storage of and access to the data depends on various factors including the data type, structure, and size, and the disciplinary domain associated with the data.  

RDMC hosts the UNC Dataverse, which is a generalist data repository available to all UNC investigators for long-term data archiving and sharing. UNC Dataverse has the desirable characteristics of data repositories for federally funded research and supports FAIR principles for findable, accessible, interoperable, reusable data.

Before making the final repository selection, the investigator should contact the repository to confirm the suitability of the repository for their project data and to determine the cost of repository fees, if applicable

The DMSP should identify the repository to be used for long-term data management and sharing. If the repository charges fees for their services, the budget and budget justification should reflect those costs. 

Selecting a Repository
UNC Dataverse

Will the project require any special provisions for data management and sharing that are not currently available at UNC-CH? If yes, please describe.

This information will help identify gaps in available data management and sharing resources at UNC. It will also help inform RMDC service and infrastructure development priorities.