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Research Data Management

This guide offers guidance and resources for managing research data in any discipline.


A Data Management & Sharing Plan (DMSP), also referred to as a Data Management Plan (DMP), is a formal document that outlines what you will do with your data during the active phase of the research project and after the project ends.  This document may also be called a Data Management Plan (DMP) depending on the funding agency.  The National Institutes of Health (NIH) refer to it as a DMSP, whereas the National Science Foundation refers to it as a DMP.  We use the term DMSP because it suggests both data management and sharing.

DMSPs are typically two-page documents. Most US federal funders and many private foundations require DMSPs to be submitted with their funding applications. Whether you are participating in a funded research project or not, writing a DMSP will help you think about the practices, people, and resources needed to manage your data.

Although funder DMSP requirements may vary, in most cases you will be asked to describe your data, other research products, and relevant software, address metadata, standards, documentation, storage, preservation, and any ethical, legal or other restrictions, and define roles and responsibilities. If applicable, you will need to discuss compliance with federal regulations protecting human subjects and privacy.

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The DMP Tool can help with writing your data management plan. It provides customized DMP forms with guidance and examples based on your research funder and research institution selections. You may use this tool to request feedback from collaborators and the UVA Library Data Management Team. If you want to request a consultation or ask a question, email us at

Below are resources to help you write your plan.

Data, Standards, and Documentation

Data and other products of research

Describe the data and other products of research to be produced from the research project. Include details about the source (e.g., sensor readings, survey results), forms (e.g., numeric, text, images, audio, video), file types (e.g., csv, txt, png, flac, mp4), and data volume. Also, indicate whether the data will change or grow in size after the research project is finished and data is submitted to a repository and if any specific software is required to analyze the data.

If you are using existing data for secondary analysis, describe the content, source and requirements for obtaining and using that data. If the existing data will be combined with data to be generated from your research project, explain the relationship between the data sets.


Funders and data repositories may require specific metadata standards or shared vocabularies to make data easier to find. Relevant data standards may also refer to areas beyond metadata or shared vocabularies, such as file formats for data exchange, guidance for data collection, or requirements for data protection. To find standards appropriate for your discipline, see Choosing and Using Metadata Standards.


Describe what documentation will be included with your data to make it understandable. Documentation may be given at three levels. Project level documentation includes the purpose of the study, research questions, hypothesis, methodology, instruments, and measurements used. File and database level documentation describes the datasets and supporting documentation. Variable level documentation defines the variables and values, particularly coded values.

For more details on metadata and documentation, see Metadata and Documentation.


Hand brushing dust off a Timbuktu manscript

Adapted Timbuktu Manuscript image by Mark Fischer with a Creative Commons Attribution-ShareAlike 2.0 license.

You will need to find a place to store your data when it is still being collected, processed, and analyzed at the research institution. Be prepared to discuss how much storage will be needed, how often data will be backed up, how data will be recovered, access control for research team members, secure data transmission from the field, and handling of information with varying degrees of sensitivity. For more details about storage, see Data Storage, Backup, and Security.

Most funders require submission of data to a repository when your research project is finished if there are no restrictions that prohibit submission. For data that will be submitted, indicate which repository will receive your research data. If the funder has its own repository or a preferred repository, use that repository. If not, your discipline may have a commonly used repository. If so, use that repository. If not, use LibraData, the UVA institutional data repository.

When choosing a repository, consider the National Science and Technology Council guidance on Desirable Characteristics of Data Repositories for Federally Funded Research. Also discuss plans for long-term retention of data at your research institution. For more details, see Data Sharing and Preservation.

Find out if your funder allows costs associated data submission in your grant budget.  Some data repositories charge fees to cover curation and preservation costs. Even if you deposit your data to a repository that does not charge a fee, consider resources you may need for preparing the data for submission, submitting the data, and responding to questions and requests from the repository.

Access and Reuse Restrictions

Data access and reuse may be restricted because of privacy protection requirements, data rights, or other reasons. Restrictions on data access or reuse should be addressed in your DMSP. Describe in your DMSP what you are going to share as well as what you are not sharing, and/or what you are sharing but only through proper de-identification and/or data use agreements.

If you have created new data from human subjects, you may need to redact your data to avoid re-identifying individuals. LibraData, the UVA data repository, requires that depositors remove any sensitive or confidential information from their data submissions. You may also determine that access to some or all your newly created data should be restricted because of data sensitivity or intellectual property claims. When submitting your data to a repository, you might have the option to recommend public access, which allows data sets to be downloaded by anyone, or restricted access, which requires researchers to request permission to access the data. You or the repository might also require other researchers might to sign a data use agreement.

If you are using existing data from a repository, a data use agreement may require that the data be shared only with certain members of your research team because of privacy requirements and then destroyed after a specified time period. If you are using existing data from a vendor through a UVA library subscription, the license probably will not allow reuse of the data for those not affiliated UVA.

Data redaction, data use agreements and vendor licenses are common examples of data access and reuse limitations. However, in some cases there may be other factors involved that restrict data access, such as informed consent language or federal, Tribal, or state laws, regulations, or policies. If you want a consultation or have questions, please contact email us at

For information about US human subjects and privacy laws and UVA Institutional Review Boards (IRBs) for compliance with federally mandated research guidelines, see Data Privacy and Human Subjects.

For information about intellectual property related to data and UVA ownership policies, see Data Rights and Policies.

Roles and Responsibilities

Indicate who is responsible responsible for overseeing data management and sharing activities and updating the DMSP. Include details about these activities (e.g., data collection, documentation, quality control, analysis, archiving and sharing) and identify who will be performing them. It may be useful to refer to this section of the DMSP when determining data and documentation access for team members.