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Research Data Management: Data Management Plans

This guide is intended to provide information on preparing a data management plan.

Introduction to Data Management Plans

A data management plan or DMP is a document that outlines how you will handle your data both during your research and after the project is completed    The goal of a data management plan is to consider the many aspects of data management, metadata generation and data preservation. A successful DMP should be completed before the project begins in order to ensure that data are well-managed during the research process as well as for preservation of the data for future use.

DMP Tool

Structure of a Data Management Plan

Each project will be different and have different types of data.  Remember that a data management plan is a living document and should be reviewed and updated regularly, especially if unforeseen data is collected. 

The recommended structure for a data management plan is as follows:

  1. Project description
  2. Survey of existing data
  3. Data to be created
    • Data organization methods (optional)
  4. Data administration issues:
    1. a. Funding and legislative requirements
    2. Data owners and stakeholders
    3. Access and security
    4. Backups
  5. Data sharing and archiving
  6. Responsibilities
  7. Budget

Data Management Checklist

There are many questions to consider when creating a data management plan.  The following list can help you to begin to think about how you will manage your data and the answers will be useful for developing the content of a data management plan.

Data Production
  • What type(s) of data will be produced?
  • What file format(s) will the data be saved as? Are those file formats proprietary? Will they degrade?
  • Will the data be reproducible?
  • Do you need tools or software to create/process/visualize the data?
Data Size
  • How much data will it be, and at what growth rate?
  • How often will it change?
Data Usage
  • Who will potentially be using your data both now and later?
Data Retention
  • How long should it be retained? (e.g. 3-5 years, 10-20 years, permanently).  Does your institution have a data retention policy?
Privacy and Security
  • Any special privacy or security requirements? e.g., personal data, high-security data
Data Sharing
  • Any sharing requirements? e.g., funder data sharing policy
  • Have you chosen a repository in which to archive your data?
Data Management Plan
  • Does your funding agency require a data management plan in the grant proposal?
Data Documentation
  • How will you be documenting your data and project?
  • What directory and file naming convention will be used?
  • What project and data identifiers will be assigned?
  • Is there a schema, ontological, or other metadata standard in your field for sharing data with others?
Storage and Backup
  • What are the strategies for storage and backup of the data?
  • Are you aware of any institutional support backups?
  • When and where will the work be published?
  • Who in the research group will be responsible for data management?
  • Who controls the data (PI, student, lab, funder)?


Sample Data Management Plans

Here are some sites that will provide you with some sample data management plans.

Data Management Plan Templates

Many organisations have put together a data management plan template.  Below is a selection of these templates.  You may find it useful to modify one of these templates for your purposes.

California Digital Library
University of Melbourne
University of Newcastle
Data Management Plan - Template (version 1) - .doc version; .rft version
Data Management Plan - Template (version 2) - .doc version; .rft version
UK Digital Curation Centre
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