Research projects often generate several data files, involve a team of collaborators, and span significant periods of time. Planning your data management contributes to a well-organized research project, saving you time and effort, and identifying roles and responsibilities for different research outputs. Although it is a good idea to begin writing a plan before the formal start of your research project, it is never too late to benefit from developing a systematic process for managing your research data.
What is a data management plan?
A data management plan (DMP) is a document you develop at the start of your research project and possibly modify through the life of your project that outlines all aspects of your data. Developing a data management plan is a vital part of your research process that helps you ensure your research data are accurate, complete, reliable, accessible, and secure both during and after your research. Data management planning also brings efficiencies to your research process, saving you time and effort by identifying any potential gaps or roadblocks early in the project.
Is a data management plan a formal requirement for my research project?
Many funding agencies, both in Canada and internationally, have begun to require data management plan documents to be submitted along with grant applications. The Canadian Institutes for Health Research (CIHR), the Social Sciences and Humanities Research Council (SSHRC), and the Natural Sciences and Engineering Research Council of Canada (NSERC) have announced an initial set of funding opportunities that require submission of a data management plan during the application stage. See the Tri-Agency Research Data Management Policy for more information. In the U.S, the National Institutes of Health have a new data management and sharing policy in 2023 and the National Science Foundation requires data management plans to be submitted along with proposals.
What key components should my data management plan (DMP) include?
Your DMP should typically describe:
- how data will be organized (folder structures, file naming conventions, file versioning);
- what file formats your data will be collected and stored in;
- how data will be described and documented during all phases of your research, including when the project is complete;
- what facilities and equipment will be required for data storage;
- what solutions and processes will be used to secure your data;
- who will have ownership and access rights, particularly if your research involves Indigenous peoples' data;
- how ethical requirements for your data will be managed;
- how data will be shared, if applicable;
- how data will be stored for the long term once your research is completed.