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This article provides guidance for researchers completing the RAMSeS IPF Data Management and Sharing section of their IPF submission and offers helpful information on drafting a DMSP that complies with funder data sharing requirements which should be considered prior to submitting your proposal.
In This Article:
Overview
The Research Administration Management Systems & eSubmission (RAMSeS) system includes 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) and Clinical Trials (CT). Questions about the categorization of your research should be directed to OSPHelp@unc.edu.
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 your data management and sharing plan (DMSP) and that the project budget includes sufficient resources to cover the cost of any necessary tools and services.
The information below provides guidance for each question in the Data Management and Sharing section in the RAMSes IPF.
Note: Prior to answering the questions below, please upload your data management and sharing plan as a separate document in the RAMSeS attachment tab. Including your plan in RAMSeS supports future implementation of your Basic Data Management Service upon project award.
RAMSes IPF Data Management and Sharing Section Questions
Have you submitted a data management and sharing plan to the Research Data Management Core (RDMC) for review?
Select Yes or No.
RDMC provides an optional, free data management and sharing plan review service to all UNC researchers. We strongly encourage requesting a review at least three weeks prior to your proposal submission deadline. Our staff will review your DMS plan for completeness, appropriateness, compliance, and feasibility, and provide feedback and recommendations as appropriate to ensure your plan sufficiently addresses funding agency and institutional data sharing requirements. A DMSP review is not required.
Request a DMSP Review
Will managing and sharing project data require dedicated personnel, specialized equipment, and/or other additional services?
Select Yes or No depending on the needs of your project.
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 your funding agency policy and guidance documents to determine which costs are considered allowable.
Will your data include any of the following? Select all that apply:
The data generated during 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. RDMC staff are available to answer questions regarding any of the categories below as you prepare your DMSP and plan for relevant activities.
Personally identifiable information (PII) or protected health information (PHI)
Researchers must always comply with applicable laws, regulations, guidance, and policies related to human subjects research and the protection of participant privacy. Your DMSP should describe specific provisions for protecting the privacy, rights, and confidentiality of study participants within the appropriate section as required by the funding agency.
Note: Researchers should not assume that data derived from human participants are exempt from data management and sharing policies.
Whenever feasible and legally acceptable, you 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.
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. Researchers 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.
Proprietary/copyrighted data
While funding agencies expect that researchers 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. Researchers are expected to comply with data use agreements, licenses, and/or applicable copyright laws that limit or prohibit data sharing. In these cases, your DMSP should describe such restrictions in detail as part of a compelling reason for limiting or refusing data sharing.
Genomic data
Some sponsors have issued additional data management and sharing policies that include expectations for projects that generate genomic data. Researchers 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 addressed in the DMSP (rather than in a separate genomic data sharing plan, which was a requirement under previous policies).
Large volume data ( >2 TB )
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.
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. Your DMSP should describe situations that may limit or preclude the ability to share project data as part of a compelling rationale for limiting sharing.
My data will not include any of the above
Select this option if none of the above categories are relevant to your research.
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 and supports FAIR principles for making data findable, accessible, interoperable, and reusable.
Note: Some sponsors may define characteristics of an appropriate repository or specify certain repositories for data deposit and sharing. Researchers should review the notice of funding opportunity/program solicitation carefully for specific data repository requirements.
Tip: UNC Dataverse is UNC's certified trustworthy generalist data repository for preserving and sharing research data. If your project qualifies for the Basic Data Management Service, you will receive a project dataverse within UNC Dataverse to either share your research data or create a catalog record that points to your data in your selected repository. UNC researchers are required to, at a minimum, create a catalog record that points to your data in your selected repository. Learn more in our
Share Your Research Data in UNC Dataverse guide.
If the funding agency does not require data deposit in a specified repository, researchers 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. Before making the final repository selection, you should contact the repository staff to confirm the suitability of the repository for your project data and to determine the cost of repository fees, if applicable. Your DMSP should identify the repository to be used for long-term data management and sharing. If the repository charges fees for their services, your project budget and budget justification should reflect those costs.
Please provide the name(s) of your selected data repository(ies) in this section. This information assists RDMC staff in implementing your Basic Data Management Service upon project award.
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. If you know of a missing resource or service that would support your data management and sharing needs, please share that information here.