Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Managing Research Data for Public Access: Data Management Plans

Data Management Plans

Data management plans describe how researchers will handle digital data both during and after a research project. Data management plans also describe how the research proposal conforms to DOT policy on the dissemination and sharing of research results.

U.S. DOT has identified five broad areas that should be addressed in a data management plan:

  1. Data Description
  2. Standards Used
  3. Access Policies
  4. Re-Use, Redistribution, and Derivative Products Policies
  5. Archiving and Preservation Plans

The National Transportation Library provides detailed guidance and writing prompts for each section, and a 2018 NTL presentation provides the overview below.


SourceNational Transportation Library.

Creating Data Management Plans (DMPs), National Transportation Library (NTL), March 2021.

► Learn more

California

Data Management Workshop, presentation, California Digital Library, UC Davis Institute of Transportation Studies, September 2018. 

Workshop topics include the U.S. DOT Public Access Plan and its requirements, guidance for writing a data management plan, best practices in managing data, and archiving and publishing data.


Iowa

Data Management Plan (DMP) Template for Iowa DOT Research Projects, Iowa DOT, May 2016.

► Related Resources: 


Missouri

Data Management Plan Template, Missouri DOT, August 2018.


Wyoming

Data Management Plan and Metadata Schema, Section 4, Wyoming DOT Research Center Guidelines, undated.

Sample Data Management Plans:

 

Sections of a Data Management Plan

Section 1: Data Description

  • Nature, scope, and scale of the data gathered in the course the project.
  • Characteristics and relationship of the data to other data.
  • Sufficient detail for reviewers about any disclosure risks.
  • Long-term value of the data.

Section 2: Standards Used

  • Anticipated formats of data and related files.
  • Use of platform-independent and nonproprietary formats.
    • What’s practicable and in accordance with practices in your field?
    • Why platform-independent and nonproprietary formats? Ensures maximum utility of the data in the future.
  • For any non-platform-independent and proprietary formats, specify the standards, formats and rationale for use.
  • Metadata standards used for data.

Section 3: Access Policies

  • Data from DOT-funded research projects must be made publicly accessible.
    • Exceptions: personally identifiable information, confidential business information, or classified information.
  • Restrictions for access and use are acceptable if deidentifying the data cannot be done while maintaining the utility of the dataset.
  • Protection of research participants’ identities and/or confidential business information.
    • How informed consent statements will be provided to participants, the steps taken to protect privacy and confidentiality prior to archiving data, and additional concerns like embargo periods for data.
    • When applicable, describe division of responsibilities for stewarding and protecting the data among PIs or other project staff.
  • For human subject research, describe how the informed consent forms will permit sharing
    • Are additional steps, such as an Institutional Review Board, required to protect privacy and confidentiality?

Section 4: Reuse, Redistribution and Derivative Products Policies

  • Who will hold the intellectual property rights for the data created by the project?
  • Will those rights be transferred to a data archive (if applicable)?
  • Does copyright apply to the data?
    • May be the case when using copyrighted instruments.
  • Indicate any enforcement of  terms of use or a requirement for data citation through a license.
  • Any legal requirements?

Section 5: Archiving and Preservation

  • How data will be archived and why that archive was chosen.
  • Archive options include but are not limited to:
    • Use of an institutional repository.
    • Use of an archive or other community-accepted data storage facility.
    • Self-dissemination.
  • Datasets must be described with essential metadata to ensures discoverability.
  • The chosen archive must support:
    • The capture and provision of the U.S. Federal Government Project Open Data Metadata Schema.
    • The creation and maintenance of persistent identifiers (e.g., DOIs, handles, etc.) and maintenance of those identifiers throughout the preservation lifecycle.

U.S. DOT Public Access Plan

Increasing Access to the Results of Federally Funded Scientific Research, Office of Science and Technology Policy, February 2013.

This memorandum is aimed at ensuring public access to scientific data for all research projects receiving federal funding. The order directs federal agencies to create a plan for improving the public’s access to the results of federally funded research. The U.S. DOT plan is below.

► Related Resource: Open Data Policy — Managing Information as an Asset, Memorandum M-13-13, Office of Management and Budget, 2013.


Plan to Increase Public Access to the Results of Federally-Funded Scientific Research Results, U.S. DOT, December 2015.

This plan laid out a strategy focused on publications, data and projects, including the requirements that all U.S. DOT-funded projects follow a data management plan and submit their research data to a publicly accessible repository.

► Executive Summary 

Related Resource Guides

Data Management Plan (DMP) Guide
Iowa State University

Research Data Management
Texas A&M University

Data Management Plans
Northwestern University

Data Management Best Practices
University of Minnesota

Data Management Plans (ENG)
University of Michigan

Data Management Plans
California State University, Long Beach

Data Management Planning for NMSU Researchers
New Mexico State University

Sample Data Management Plans

Project Level: Sample data management plan, Iowa DOT.

Program LevelData Management Plan, Info, & Guidance, National Center for Sustainable Transportation.

More Samples: Sample data management plans from various institutions can be found in the U.S. DOT Public Access Data Management Plans collection. Sample plans from across scientific disciplines can be found at Public DMPs.

Additional Resources

DMPTool.org 

ROSA P: How to Submit Datasets
National Transportation Library

Persistent Identifiers
National Transportation Library

Procedures for Digital Object Identifiers
National Transportation Library