Elements of a Data Management Plan


Several funding agencies require or encourage the development of data management plans for research. You should review specific guidelines for data management planning from the funding agency with which you are working. Because some funding agencies do not provide specific guidelines, below is an abbreviated compilation of data management plan elements from several sources (see DMPTool).


Roles and Responsibilities

  • List staff/organizational roles and their responsibilities for carrying out the data management plan (DMP); name specific people where possible. Include a description of time allocations, training requirements, and contributions of non-project staff, as appropriate.
  • Indicate when and/or how often adherence to your DMP will be checked and/or demonstrated. Include the names of the person(s) responsible for adherence to your DMP.
  • Indicate who/which roles will assume responsibility for carrying out the DMP should personnel changes occur or if the PI leaves the institution. Describe the process for transferring responsbility for the data.
  • Indicate who will have primary responsibility for how the data will persist over time when the original personnel are no longer associated with the project.
  • See Examples

Types of Data

  • Provide a short description of the data that will be generated in the research project (e.g., samples, physical collections, software, curriculum materials, and other materials to be produced during the course of the project). Include an estimate of the amount of data and content of the data (if possible).
  • In the case of software, contact NCSU's Office of Technology Transfer (OTT) to review considerations for software generated in your research.
  • Describe the data types will you be creating or capturing (e.g. experimental measures, observational or qualitative, model simulation, processed etc.).
  • Describe how the data will be created or captured.
  • Indicate if you will be using existing data and describe the source of that data. Also describe the relationship between the data you are collecting and the existing data that you are integrating into the project.
  • See Examples

Data Formats and Metadata

  • Indicate which file formats you will use for your data, and why you will use those formats.
  • Describe any contextual details (metadata) that are necessary to make the data you capture or collect meaningful to you and others.
  • Describe how you will create or capture these contextual details.
  • Describe the form that the metadata will take (i.e., which metadata standards, if any, will be used). Where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies.
  • Explain why have you chosen particular standards and approaches for metadata and contextual documentation (e.g., recourse to staff expertise, Open Source, accepted domain-local standards, widespread usage).
  • Describe the procedures that will be used to ensure data quality.
  • See Examples

Access, Sharing and Privacy

  • Describe which data will be shared and how you will make the data available including any resources needed such as equipment, systems, expertise, etc.
  • Indicate when you will make the data available (including any factors such as embargo periods for political, commercial, patent reasons, or complying with publishing policies).
  • Describe the process for gaining access to the data. Be aware that some journals require data access upon publication (e.g., PLoS).  Indicate if you will use a repository, if the data will be available as supplementary files with the publication, or if the data will be available upon request (for PLoS, you will need to identify the group to which requests should be submitted as an individually named authors are not sufficient for PLoS' data availability policy).
  • Indicate if you anticipate that the original data collector, creator, or principal investigator retains the right to use the data before opening it up to wider use.
  • Indicate if there are any ethical and privacy issues related to sharing the data. If so, describe how those will be resolved if the data is shared (e.g., removing any personally identifying information in the data, working with institutional ethical committees, resolving potential conflicts by way of formal consent agreements).
  • If applicable, describe what you have done to comply with your obligations in your IRB Protocol.
  • If you need help with intellectual property and copyright issues, contact NCSU's Copyright and Digital Scholarship Center.  In the case of software, contact NCSU's Office of Technology Transfer (OTT) to review considerations for software generated in your research.
  • Describe how the dataset will be licensed if rights exist (e.g., list any restrictions or delays on data sharing needed to protect intellectual property, copyright or patentable data).
  • See Examples

Policies and Provisions for Re-use & Re-distribution

  • Indicate if any permission restrictions need to be placed on the data.
  • Describe which communities/groups are likely to be interested in the data.
  • Describe the intended or foreseeable uses and users of the data.
  • Indicate if there any reasons not to share or re-use data (e.g., ethical, non-disclosure, etc.). Please refer to "Sharing Data" for more details.
  • See Examples

Data Storage and Preservation

  • Describe the long-term strategy for maintaining, preserving and archiving the data. Describe the procedures that your intended long-term data storage facility has in place for preservation and backup.
  • Indicate which archive, repository, central database, or data center you have identified as a place to deposit the data.
  • Describe the transformations that will be necessary to prepare data for preservation and/or data sharing (e.g., data cleaning, normalization, or removing personally-identiying information where appropriate).
  • Describe the metadata and/or documentation that will be submitted alongside the data or created when the data is deposited in order to make the data discoverable and/or reusable.
  • Describe the set of conventions that you will use for naming data files and folders, and how you intend to manage multiple versions of files. For specific suggestions, see Data Storage and File Naming
  • Indicate any related information that will be deposited (e.g., references, reports, research papers, fonts, the original bid proposal, etc.).
  • Indicate how long will/should the data be kept beyond the life of the project. Many grant funders suggest that the minimum data retention period for research data should be 3 years after conclusion of the grant award or 3 years after the data is released to the public (whichever is later).
  • See Examples


  • Check with the funding agency to determine where in the proposal to include costs related to data management.
  • Include any costs for data management services.
  • Include any anticipated income from licensing data.
  • Include any costs for managing data during the course of the project as well as after the project is complete.
  • See Examples


DMPTool: Create ready-to-use plans

We are proud to offer the DMPTool as a resource for the NCSU research community. Developed by the California Digital Library and a group of major research institutions, the DMPTool is designed to help researchers:

  • Create ready-to-use data management plans for specific funding agencies
  • Get step-by-step instructions and guidance for data management plans
  • Learn about resources and services available at their home institution to fulfill the data management requirements of their grants

To access the DMPTool, visit https://dmptool.org/user_sessions/institution and choose the "North Carolina State University" from the pull-down menu. From there you can log in with your Unity ID and password.


The content on this page is adapted from the University of Virginia.