Guidance for planning, documenting, reviewing, and supporting research data management plans for Microbiology and Immunology projects.
On this page
About data management plans (DMPs)
A data management plan (DMP) is a written document that describes the data you expect to acquire or generate during a research project, how you will manage, describe, analyze, and store those data, and how you will share and preserve them when the project ends.
Writing a DMP helps formalize your approach, identify gaps early, and keep a record of what your team intends to do. Data management is best addressed at the start of a project, but it is never too late to create or revise a plan.
Why create a DMP early?
- Clarify expectations: Document how data will be collected, named, stored, described, and preserved before project complexity grows.
- Reduce risk: Identify privacy, security, backup, and retention gaps early so they can be addressed before problems appear.
- Support funding readiness: Many granting programs expect research data management planning as part of a complete proposal package.
Requirements, examples, and review
Funding agency requirements may apply. Many funding agencies require a DMP with grant applications. The federal Tri-Agency research data management policy framework has made DMP planning increasingly important for funded research.
Funding agency requirements
UBC research support teams maintain guidance on data management and sharing expectations across major funding agencies. A good starting point is the SPARC comparison resource together with the Tri-Agency policy material.
Sample agency-specific plans
- ICPSR sample DMP for social and political science data
- NEH-ODH successful grant application examples
- NIH data-sharing plan examples
- NSF Biology Directorate sample plans
- NSF directorate examples from UC San Diego
DMP review support
MBIM IT, ARC Consult, and UBC research data support can help review your plan and identify technical, storage, or process issues before submission.
Creating a data management plan
A DMP is a living document
Research changes over time, and your DMP should change with it. Review the plan whenever collection methods, storage locations, privacy requirements, sharing expectations, or collaborators change.
Preparing to write a DMP
Before drafting, think through storage, backup, metadata, access controls, and any sensitive data requirements. This also assumes you have completed the required UBC Privacy Matters training.
- Privacy Matters training
- Including IT costs in research grants
- Data storage and backup
- Data best practices
- Creating metadata
- Working with sensitive data
- Data sharing guidance
- cIRcle, Globus Plus, Microsoft 365 OneDrive, MS Teams, and MSL Warehouse
- Licensing your data
- Data preservation using online repositories
The Stanford/California Digital Library DMPTool and the Portage DMP Assistant both provide guided workflows for creating ready-to-submit plans tailored to funders and research contexts. See Stanford DMPTool information and UBC DMPTool access information.
DMP submission
Once your DMP is complete, include it with the rest of your proposal package according to the requirements of the relevant funding agency.
Training resources for data management
UBC Library research teams maintain training materials that support digital scholarship, research data management, citation management, GIS, and data analysis workflows.
- UBC Library Research Commons resources
- Full training resource index
- Core skills in digital scholarship
- Data analysis and visualization
- Geographic information systems (GIS)
- Research data management
- Citation management
UBC research data management abstracts and session slides
Reference these sessions when building or refining your research data management approach:
- Intro to RDM
- First Steps in Data Management Planning
- Intro to the DMP Assistant
- Re-introduction to the Data Life Cycle
- Intro to the Open Science Framework
- Intro to Data Repositories
- Intro to Dataverse
- Data Discovery & Deposit Using FRDR, Geodisy, and Globus
- Intro to REDCap
- Intro to Sensitive Data and De-identification