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Research Data Management

What is a Data Management Plan

A data management plan (DMP) is a written document that describes the data you expect to acquire or generate during the course of a research project, how you will manage, describe, analyze, and store those data, and what mechanisms you will use at the end of your project to share and preserve your data (Source: Stanford University Libraries)

Data Lifecycle illustration

Above: Data Lifecycle illustration  Source: American University of Beirut Research Data Services Libguide: http://aub.edu.lb.libguides.com/data_services

 

A DMP is required as part of your grant proposal by many funders, BUT planning for good data management, data sharing, and data preservation should be a part of your project plan and integrated throughout the workflow. Plan for this at the same time you write your DMP. To learn more about best practices for good research and data organization and writing DMPs:

  • See the information in this guide 
  • Use the Data Management General Guidance from the DMP Tool

 

What is in a DMP?

While the basic format of a Data Management Plan will be similar from funder to funder, each funder may have specific sections of information that they require.

The DMPTool has templates and requirements for many funders available on their site. As they state, "Templates for data management plans are based on the specific requirements listed in funder policy documents. The DMPTool maintains these templates, however, researchers should always consult the program officers and policy documents directly for authoritative guidance. Sample plans are provided by a funder or another trusted party."

The sections of most DMPs will include information similar to this: 

  • Types of data - what are you producing or collecting?
  • Formats and standards - What file formats will the data be in? Is there a particular type of text format or a standard recording measure for your data?
  • Roles and responsibilities - Who in the lab will do what? Who will be collecting the data? Is that the same person that will analyze it? Will there be members of the project from outside your institution?
  • Dissemination of results - Will you be publishing an article? How else will your results be shared?
  • Data sharing, public access and reuse - Will you deposit your data in a disciplinary repository? Will it be available for public reuse?
  • Privacy, confidentiality, security, intellectual property rights - If there are many people in your lab, who will have access to what parts of the data? How will you keep the lab as a whole secure? Who owns the rights to the data? It could be the PI or the institution in some cases, and this is important to know. 
  • Archiving data, samples, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education.  - where will this information be stored long-term after the project ends? Will you be able to access it in five years if someone requests your data?