Science (General)

When conducting research, it is valuable (and often required) for investigators to develop plans for the curation, access, and preservation of their data. The U-M Library offers multiple forms of support in this endeavor; we highlight selected resources and the basic items to include in a such a plan below:

Roles & Responsibilities: Often a DMP will require an accounting of who will accept responsibility for tasks associated with data management.  DataONE offers best practices in assigning roles and responsibilities.

Expected Data: Be able to describe (roughly) how much data your project will generate, at what rate, and if it will be generated as multiple data sets. Note also how much of that data will be retained and why. 

Metadata and Standards: Think about how you will describe the data in such a way that you and others will find meaningful.  Often there are industry or community standards that should be used to ensure that your data can work with other data and are accessible by other researchers.

Formats: Describe the file formats of your data.  Whenever possible, data should be stored in stable, non-proprietary formats, preferably those based on open and published standards. 

Retention: Think about how long you want your data to be available.  Often there is a minimum requirement by the funding agency of 3, 5, or more years.  

Dissemination: Explain if, how, and when your data will be available. You may be able to offer the data from a repository like Deep Blue Data, or you may need to require a request to the project PI.  

Preservation: A key part of any DMP is describing how you will preserve your data.  It is good to plan on several preservation and back-up options.  When putting your data in a repository, note their commitment to long-term preservation and curation of the data.

Data Management Plan Resources listed above will provide you with more detailed descriptions of and resources for the above topics.