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Research Data Management

Overview of Data Management Plans

What is a data management plan?

A data management plan is a document that explains how data will be collected, organized, stored, and documented throughout the life of a research project. DMPs also provide information about how research data will be shared with other researchers and the general public, and how the data will be handled to guarantee its long term preservation.

Many research funders have begun to require the inclusion of DMPs in all funding proposals. However, DMPs have benefits for all research projects, even when they are not a requirement. DMPs can help you ensure that all members of your research time handle data in the same manner. This makes it easier to find the data you are looking for. They also make it easier to refer to your data later or, or for other researchers to understand and benefit from your research.


Funding agency requirements

Many funding agencies require that applicants submit data management plans with all funding requests. SPARC (the Scholarly Publishing and Academic Resources Coalition) maintains a searchable collection of data sharing requirements for U.S. federal agencies. Non-federal funding agencies may also have data sharing requirements. Before you begin creating your data management plan, familiarize yourself with your funder's specific requirements. 

Creating Your Data Management Plan


The DMPTool is a free, open source, online resource that helps researchers create data management plans. The tool includes a click-through wizard for creating data management plans that comply with funder requirements. It includes templates for many popular funding agencies which can help you make sure you are meeting your funder's specific requirements. If your funder is not listed on DMPTool, or if you do not have a funder, the tool also provides generic templates that can be used. 


Components of a Data Management Plan

The components of your specific data management plan will depend on the nature of your research project and any funder requirements to which you may need to adhere. However, there are some common components to data management plans. It may be useful to think about these before you begin writing up your plan. 

Data Types and Collection
  • What type(s) of data wil be collected or generated? (Observational, experimental, derived or compiled, etc.)
  • What form does the data take? (Text, numeric, audiovisual, geospatial, etc.)
  • How will this data be collected or created? (Sensor readings, model simulations, text mining, etc.)
Metadata and Documentation 
  • What file formats will your data be stored in? (.txt, JPEG, MP4, etc.)
  • What form will your documentation and metadata take?
  • Which metadata standards will you use? 
  • What background or contextual information is needed to make your data usable and interpretable by others? 
Storage and Backup
  • How wil your data be stored and backed up during your research project?
  • Who is responsible for maintaining storage and backup?
  • How will you manage access and security?
Sharing and Archiving
  • Which data are of long-term value and will be retained, shared, and preserved? 
  • What resources will future researchers need to make use of your data? (E.g. is proprietary software required?)
  • How will you share your data?
  • Are there any restrictions on what data can be shared?
  • Who is responsible for ensuring the data management plan is followed? Is there a plan in place if this individual leaves your project?