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Research Services

Data Management and Sharing

Data Sharing Policies

In May of 2022, The White House, by guidance of the Subcommittee on Open Science of the National Science and Technology Council, released "Desirable Characteristics of Data Repositories for Federally Funded Research." This document aims to improve consistency across Federal departments and agencies in the instructions they provide to researchers about selecting repositories for data resulting from Federally funded research. It identifies a set of desirable characteristics of online, public access data repositories to help ensure that research data are findable, accessible, interoperable, and reusable (FAIR) to the greatest extent possible, while integrating privacy, security, and other protections. 

All Federal sponsors require a Data Management Plan. We advise that you research your sponsors' most current Data Management Policies and tailor your Data Management Plan accordingly. Whether or not you are required to share data online, consideration of the questions that underlie a data management plan can assist with project management and annotation, reduce errors, assist with data collection, and reduce the work required to prepare data should it be requested by researchers.

Creating a Data Management Plan

The 2023 NIH Data Management and Sharing Policy recommends that the DMS plan be two pages or less in length and include the following elements:

  • Data Type: A brief description of the scientific data to be managed, preserved, and shared. For any ethical, legal, or technical factors that may limit sharing, the DMS plan should include a rationale for limiting data sharing.
  • Related Tools, Software, and/or Code: An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, the name(s) of the necessary tool(s), and how the tools can be accessed.
  • Standards: A description of the standards, if any, that will be applied to the scientific data and associated metadata.
  • Data Preservation, Access, and Associated Timelines: Plans and timelines for data preservation and access.
  • Access, Distribution, or Reuse Considerations: A description of any applicable factors affecting access, distribution, or reuse of scientific data related to privacy, security, informed consent, and proprietary issues.
  • Oversight of Data Management and Sharing: An indication of how compliance with the plan will be monitored and managed, frequency of oversight, and by whom.


2023 Changes to NIH Policy

As of January 25, 2023, the new Data Management and Sharing Policy announced by the National Institutes of Health (NIH) will be in effect, replacing the 2003 NIH Data Sharing Policy. The 2023 Data Management and Sharing Policy requires all grant applications and proposals to include a data management and sharing (DMS) plan describing how scientific data generated or used in funded research will be managed and shared. Acknowledging costs associated with data management and sharing activities, the new DMS policy also establishes guidelines for including these costs in funding applications.

The DMS plan is a formal document that describes the scientific data to be generated or used in research projects and outlines specific provisions for ensuring that the data are FAIR: findable, accessible, interoperable, and reusable. Importantly, FAIR data are data that are stored properly as they are being generated and analyzed, accompanied by comprehensive documentation to support understandability, and archived in a trustworthy repository for sharing and long-term preservation. The DMS plan should reflect this standard.

The NIH DMS policy underscores the value of scientific data and the critical role of data management and sharing to sustain and maximize this value. Proper data management and sharing enables the scientific community to verify, extend, and build upon research results. The policy also presents an important opportunity for investigators to adopt data management and sharing activities as part of normative research practices, which is key to upholding scientific rigor and integrity, accelerating the pace of research discoveries, and promoting public trust in science.