Making a data management plan

A data management plan (DMP) is a document that describes:

  • What data you expect to acquire or generate during a research project
  • How the data will be collected, documented, analyzed, stored, preserved and shared during the project
  • Who will be responsible for managing the data throughout the project
  • When data management activities occur throughout the project

Why a data management plan

Icons describing data management planning steps.

Write a data management plan

For best practice and step-by-step guidance in creating a data management plan, use:

  • DMP ASSISTANT to create data management plans for Canadian funders (select University of Manitoba template)
  • DMP TOOL to create data management plans for US funders, such as NIH or NSF

The University of Manitoba DMP template is available at the DMP Assistant with the components listed below. The guidance that accompanies each question in the template directs you to UM specific resources and support. Registration for an account in DMP Assistant is free.

Components of a data management plan

  • Data collection
    • Define data types: textual, tabular, graphical, numerical
    • List the file formats that will be used/created: proprietary, open standard. Software or tools required to read and/or view the data
    • Naming conventions for versions, data architecture: documentation in READ ME file, root name
  • Documentation and metadata
    • Define the documentation accompanying the data generated
    • Outline best practices to ensure accuracy, consistency of documentation
    • Define metadata standard(s) to be used
  • Storage and backup (during project)
    • Define backup process - see best practice for backup
    • Outline total storage requirements (e.g. megabytes, gigabytes, terabytes) and length of retention time
    • Access and location: details of access (protection of sensitive data) and documentation
  • Data preservation (after project)
    • Using deposit with a permanent identifier assigned is preservation best practice
    • Elaborate on retention: duration, format, location, access parameters
    • Describe preparation processes: data selection, de-identification, data formats
  • Data access and reuse
    • Stipulate the version of data (raw, processed, analyzed, final)
    • Method of storage and access - resource and access considerations
    • Levels of access: free to read v. ability to reuse
  • Responsibilities and resources
    • Describe the various types of access, duration that will be granted, and how it will be documented
    • Outline the costs related to the data management lifecycle, including equipment, software, dissemination (including any journal article processing charges) - see the Data Management Costing Tool for estimating what those costs may be
  • Ethics and legal compliance
    • Sensitive data: describe your management processes to ensure security and restrict access
    • Strategies for reuse: your data selection criteria, documentation; method(s) to enable access e.g. deposit
    • Identify any/all ethical, legal and intellectual property considerations that may override access, and/or reuse to the data and what processes you have undertaken to manage them

Data management plan resources

Portage Network
Inter-university Consortium for Political and Social Research (ICPSR)
Cambridge University