A data management plan (DMP) is a document that describes the data governance policies within each group or project (i.e. how data are documented, organized, stored, and shared). This ensures that the appropriate researcher(s) will be able to safely and securely access and analyze the data across the activities of a research group or at each project phase.
Data Management Online Learning
Please see some selected Online Training Modules concerning Data Management from the Duke University Libraries. Additional videos can be found in the “Related Resources” section of this page under “Training and Job Aides.”
- Research Data Management Overview
- Data Management 101 for Humanists
- Meeting Data Management Plan Requirements
Creating a data management plan
Data management plans:
- are highly useful for planning ahead to ensure there are appropriate resources available,
- function as a reference guide for the entire research team throughout the project duration, and,
- are required by several funders as a component of the funding proposal.
Developing sound strategies for storing and organizing data prior to beginning the project also supports study reproducibility and end-of project goals, such as publication and data sharing.
Plans can either be “General” to cover all research activities that a research group engages in or “Project specific” which describes in greater detail the data management expectations of a specific research inquiry, and is often the type of plans that funders require as part of their funding proposal.
Data Management Plan Examples
Example DMPs are provided below with permission. Please note that these are “general” DMPs.
Considerations for developing your data management plan
Using the DMP tool
Duke participates in a program to allow researchers access to the DMPTool to develop data management plans. Research teams can access the integrated guidance resources, funder templates, and access Duke specific templates and consultation through Duke Libraries.
- When you access the DMPTool, select the “Get Started” button.
- Select “Your institution” under sign-in option 1.
- Select Duke University from the institutions list to log-in with your NetID and password.
- Select "Create a Plan" and check "No funder associated with this plan" and Duke’s data management guidance suggestions and best practices will automatically populate the tabs.
Each tab walks the user through sub-sections of developing a data management plan. On the right-hand side for each section, discover best practices and considerations for what should be included in that section of the plan.
Under the “Request Feedback” tab, you can request Duke Libraries to review and provide feedback on your plan during any point of development. There is usually a three-day turnaround to receive feedback.
Roles and responsibilities
Who will be involved in your project during each stage of the data life cycle?
- Collecting or obtaining the data
- Performing quality assurance checks of the data
- Cleaning and curating the data
- Analyzing the data
- Archiving and sharing the data
What is each team member’s role within each stage and will they need additional training to carry out those responsibilities?
Research methods and data description
What data are essential to the aims of your research project? How are you obtaining this data or what are the data collection methods?
- Access the Plan the project and methodology page for consultative project planning services.
If you are using secondary data, do you understand the data classification?
How will the data be analyzed?
- Access the Design the analysis plan page for qualitative and quantitative consultations and support.
Storage and organization workflow
What storage solution(s) will you USE and is it appropriate for the type and size of your data?
- Access the Determine compute and data storage solutions page for more information about data storage options.
Does the storage solution provide an automatic backup, or do you need a backup storage method?
How will you maintain version control of data and files?
Documentation and metadata
How will you structure and label files in a way so the data may be easily reused or reproduced?
What metadata standards are commonly used in your discipline? How will you apply these to your project?
Data sharing and archiving
Are there any data sharing requirements or limitations from the funder or stated within collaborative agreements?
- Access the Engage in open science and open scholarship page for more information about data sharing and institutionally-support repositories.
For human subjects data, how will you ensure all data are appropriately de-identified?
How will you archive the data and is the archival solution appropriate for the types of data sets?
- Access the Archive data and documents page for more information about archival options.
At Duke University there are a number of private and federal funders who provide support to research activities across the university. Increasingly, both federal funders and private funders are requiring Data Management Planning in some form or another as a required part of their research project funding.
As mentioned above, the DMPTool can provide funder specific templates for you to use when creating your plans. Otherwise, you may reach out to the Duke Office of Scientific Integrity or the Center for Data and Visualization Sciences (CDVS) for help with funder specific data management plans using the “Related Resources” section on this page. In addition, the DMPTool has a page listing out links to the individual funder requirements.