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Data Management

How to manage research data to meet funder requirements and facilitate your research

What is a Data Management (and Sharing) Plan?

A data management plan (also known as a data management and sharing plan, depending on the funder) typically contains information about the following:

  • Data types: The type and amount of data that will be generated by the research
  • Storage and access: How and where the data will be stored, secured, and accessed in the course of research
  • How the data will be made FAIR (findable, accessible, interoperable, and reusable), for instance whether there are standards for collecting and documenting your type of data that would allow it to be easily integrated with existing datasets.
  • Sharing: Where and when the data will be publicly shared
  • Accountability: Who is responsible for executing the plan, training project team members on data workflows, etc.
  • Special considerations: Personal or otherwise sensitive information in the data and how it will be protected

Different funding agencies have different specific requirements for the content and format of data management plans. DMPTool is an excellent resource that will guide you through creating a data management plan tailored to your granting agency.

Help For Writing a DM(S)P

DMPTool is an excellent resource that will guide you through creating a data management plan tailored to your granting agency. DMPTool is actively kept up to date and reflects the latest policies of major funders.

DMPTool tips:

  • Simply create a free account using your preferred email address (Wesleyan SSO is not set up for the DMPTool) and click "Create a new plan" to begin.
  • The right-hand sidebar includes guidance from the funding agency as well as from the DMPTool creators. Make sure to click on the DMPTool tab to access their guidance, which is more detailed, complete, and useful than the funder guidance.
  • DMPTool users can choose to make their DMPs public. Note that the public DMPs on DMPTool are not curated and are not necessarily good examples. Scroll down for a curated selection of DMPs.

Wesleyan provides tools and expertise that you can and should include in your DM(S)P as relevant. These include a range of data storage options and our institutional data repository Figshare for publishing data. We also have a range of experts of campus that you are encouraged to consult about how to use these tools, plan out your data collection for effective processing later on, and more. See the Wesleyan Resources tab for more.

A librarian can provide feedback on draft data management plans. Simply email your draft DM(S)P along with your grant proposal abstract and the name of the funding agency to reference@wesleyan.edu. Please allow one week for turnaround.

 

Have a resource you think we should add? Let us know.

Budgeting

Costs associated with your data management plan, such as the cost of storage space or data archiving and even the cost of labor to manage data, are generally allowable uses of your grant funding. It is essential to think through these costs ahead of time so that you can budget for them in your grant proposal.

Storage and preservation costs

If your research data will be on the order of MBs to tens of GBs, existing storage and archiving solutions that are free to the public or the Wesleyan community will likely meet your needs (see the ITS storage options grid). However, if your data will be on the order of hundreds of GBs or more, you may need a different solution with associated costs. To discuss working storage solutions, contact ITS. To discuss long-term sharing and preservation solutions, contact the library's WesScholar and Digital Preservation team.

Example DM(S)Ps

The Working Group on NIH DMSP Guidance has put together a database of over 150 real DMPs from a wide range of disciplines and topics "compiled from researchers, institutions, libraries and workgroups who shared their data management plans online from 2012-2022." Use the search function to find DMP examples in your field (e.g. "chemistry", "anthropology") or that discuss a similar data type (e.g. "survey", "spectrometry", "video").