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Archives Home > UWM Records Management > Data Management Plans

Data Management Plans

In May 2010, the National Science Foundation announced that effective January 2011, all grant proposals would need to include a Data Management Plan as part of the application to be considered. Faculty and staff Research data is generally not considered to be a public record under the Wisconsin Public Records Law, but the principles for managing data for NSF or other grantmaking institutions are similar to records management principles. UWM Records Management is happy to assist you with creating and implementing your data plan. For more detailed information, please see UWM's main data plan site, or contact Kristin Briney, Data Services Librarian.

Additional information about data management policies and resources in a UWM-specific context may be found here. See also the slides from Data Management Bootcamp, an intensive training program held at UWM June 19-21, 2012.

Two additional resources of potential use to UWM Researchers:

  • DMPTool: A California Digital Libraries Initiative that provides templates and links to resources for writing Data Management Plans for a number of granting agencies, including NSF, NIH, the NEH Office of Digital Humanities, and the Institute of Museum and Library Services. You will need to create a free account to use the tool. UWM offers Shibboleth authentication for easier login with DMPTool.
  • Digital Curation Centre: A central hub of resources for managing, sharing, and storing research data, including articles and best practices. Of particular interest to researchers is the Tools and Services Catalogue, which links to and provides reviews of various tools for curation, visualization, and long-term storage and sharing of research data.


Before you create your data plan

Before writing your data management plan, you will need to take stock of your data management requirements. You should, at minimum, be able to answer the following questions:

  • What kind of data am I producing? What file formats will the data be saved in? Do I need special software or hardware to read the data?
  • How much data am I creating? What is my expected rate of data creation? What will be my storage needs once all of the data has been created?
  • Who will use the data? Who will have access to the data during its primary use, and who may want access for secondary use? Do I need a data dictionary or other documentation to make sense of the data?
  • What are my retention requirements? Are these requirements for personal use, or is there a field or journal-specific retention period? (Note that the NSF suggests a minimum retention of 3 years for most types of data.)
  • Are there any ontologies or specialized metadata for the type of data you will be producing? How will you mark up your data to fit these ontologies?
  • What are the requirements for sharing my data? Are these requirements mandated by the granting agency, the journal of publication, a specific field's best practices, or some other source? How will I make my data available to fulfill this requirement?
  • What is the long-term research value of my data? How much of it, if any, should be archived for permanent preservation?
  • What are my security requirements? Does my data contain human subject information or proprietary/patent-related information? How does this affect my sharing and retention requirements?

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Writing your data management plan

Your data plan, which should be no more than two pages in length, should incorporate as many of the answers to the above questions as possible. NSF's grants manual has five components that must be included in any data plans submitted to that agency:

  1. The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
  2. The standards to be used for data and metadata format and content. (Where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies.)
  3. Policies for access and sharing, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
  4. Policies and provisions for re-use, re-distribution, and the production of derivatives.
  5. Plans for archiving data, samples, and other research products, and for preservation of access to them.


Iindividual directorates may have additional requirements for their data management plans. Please see for more information.

The University of Wisconsin-Madison has a few examples of data plans developed and submitted under the NSF requirements.

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Sharing your data

In the vast majority of cases, you are under no obligation to share data until you have published the associated article or monograph, assuming that the time-lag between the completion of your dataset and publication is reasonable in length. Once you are prepared to share your data, you have a number of options available to you:

  • Direct sharing via e-mail or PantherFILE. This method is best for relatively small amounts of data. Exposure of your data to the wider community will be very limited. Most journals will require that you include contact information if you will be sharing data this way.
  • Publication in UWM Digital Commons. This sharing option is best for large, discrete data sets and files in common formats. Digital Commons is not a secure environment, so this is not an appropriate choice for sensitive data. The UWM Archives will assist you with creating an account and uploading your data if you choose this option.
  • As supplementary materials in the journal of publication. Not all journals will provide this service, so be sure to check before relying on this method as a means of data sharing. Additionally, journals may not have the resources or inclination to store data sets for long periods of time.
  • In a discipline-specific data repository. A partial list of repositories is available via Databib. This method may be best for creating the widest exposure for your data, but as with journals, repositories may or may not be able to retain your data long-term. Your discipline's subject librarian may be able to help refer you to the most appropriate repository.

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Storing your data

Depending on the size and long-term value of your data, you have a number of options for storing it during or after the period in which you are required to share it. Most of these are described at the Graduate School's Data Storage page, and at UW-Madison's data plan site. Please consult your department's IT staff, UITS's main research computing staff, and/or the Archives for assistance with determining which storage option is right for you.

Regardless of which option you choose, you should follow the UWM Records Management guidelines for long-term storage of records and for ensuring your digital records comply with Wisconsin Administrative Rule 12. If your data requires a data dictionary, codebook, or any special hardware or software, be sure you make provision for preservation of that material as well, or else develop a migration or emulation plan to ensure your data remains readable over the long-term.

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