What is DMPTool?
With DMPTool you can create and share data management plans. It provides step-by-step guidance for creating your own DMP, including templates and sample plans to help you address requirements specific to Harvard and your funding sources.
Using DMPTool at Harvard
Harvard is a DMPTool partner institution. Log in using your Harvard credentials.
- Go to DMPTool. Select Get Started.
- Select Harvard University from the menu of DMPTool partner institutions, then select Next.
- Enter your Harvard credentials when prompted.
WHAT IS A DATA MANAGEMENT PLAN?
A data management plan, or DMP (sometimes also called a data sharing plan), is a formal document that outlines what you will do with your data during and after a research project. Most researchers collect data with some form of plan in mind, but it's often inadequately documented and incomplete. Many data management issues can be handled easily or avoided entirely by planning ahead. With the right process and framework it doesn't take too long and can pay off enormously in the long run.
Many funding agencies, especially government funding sources, require a DMP as part of their application processes. Even if you are not seeking funding for your research, documenting a plan for your data is a best practice and will help your data comply with Harvard's policies for responsible data management. If your DMP provides for your data to be openly shared, the data necessary for external replication of your research findings will be available to the research community for the long term.
What do I include in a DMP?
Information contained in a data management plan describes your plan for addressing many aspects of working with data. A DMP doesn't need to be long. It should include things like:
- Types of data: What is the source of your data? In what formats are your data? Will your data be fixed or will it change over time? How much data will your project produce?
- Contextual details (metadata): How will you document and describe your data?
- Storage, backup and security: How and where will you store and secure your data?
- Provisions for protection/privacy: What privacy and confidentiality issues must you address?
- Policies for re-use: How may other researchers use your data?
- Access and sharing: How will you provide access to your data by other researchers? How will others discover your data?
- Archiving and providing access: What are your plans for preserving the data and providing long-term access?