What is a data management plan (DMP)?

Every good project begins with a plan. Planning for data management involves the active organization and maintenance of data throughout the research process, and suitable storage, disposition, or sharing of the data at the project’s completion.

Best practices in data management

This brief guide presents a set of good data management practices that researchers can adopt, regardless of their data management skills and levels of expertise.

The following DMP Exemplars cover a range of disciplines and research methods, highlight best practices for DMPs in those disciplines, and provide a reference point for researchers writing their own DMPs.

Digital Humanities
Data Management Plan: Soundscape Study

Mixed Methods
Data Management Plan for Mixed Methods Fictional Exemplar

Natural Sciences
Data Management Plan for Computational reproducibility in High-Performance Computing (HPC)

Social Sciences
Data Management Plan for People, Places, Policies and Prospects: Affordable Rental Housing for Those in Greatest Need

Additional Exemplars are available on the Portage Training Resources page, under DMP Exemplars.

DMP Assistant is a bilingual tool for preparing data management plans (DMPs). The tool follows best practices in data stewardship and walks researchers step-by-step through key questions about data management.

Sections of the DMP	Questions
Data Collection	What types of data will you collect, create, link to, acquire and/or record? What file formats will your data be collected in? Will these formats allow for data re-use, sharing and long-term access to the data? What conventions and procedures will you use to structure, name and version-control your files to help you and others better understand how your data are organized?
Documentation and Metadata	What documentation will be needed for the data to be read and interpreted correctly in the future? How will you make sure that documentation is created or captured consistently throughout your project? If you are using a metadata standard and/or tools to document and describe your data, please list here.
Storage and Backup	What are the anticipated storage requirements for your project, in terms of storage space (in megabytes, gigabytes, terabytes, etc.) and the length of time you will be storing it? How and where will your data be stored and backed up during your research project? How will the research team and other collaborators access, modify, and contribute data throughout the project?
Preservation	Where will you deposit your data for long-term preservation and access at the end of your research project? Indicate how you will ensure your data is preservation ready. Consider preservation-friendly file formats, ensuring file integrity, anonymization and de-identification, inclusion of supporting documentation.
Sharing and Reuse	What data will you be sharing and in what form? (e.g. raw, processed, analyzed, final). Have you considered what type of end-user license to include with your data? What steps will be taken to help the research community know that your data exists?
Responsibilities and Resources	Identify who will be responsible for managing this project's data during and after the project and the major data management tasks for which they will be responsible. How will responsibilities for managing data activities be handled if substantive changes happen in the personnel overseeing the project's data, including a change of Principal Investigator? What resources will you require to implement your data management plan? What do you estimate the overall cost for data management to be?
Ethics and Legal Compliance	If your research project includes sensitive data, how will you ensure that it is securely managed and accessible only to approved members of the project? If applicable, what strategies will you undertake to address secondary uses of sensitive data? How will you manage legal, ethical, and intellectual property issues?

Key resources

File naming conventions and versioning

Metadata standards

Storage, active data backup, and security: Computational Resources (PDF, 551KB)

How do I manage individual participant data, or data with other privacy restric…