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Research Data Management

Data Management Plans

Data management plans (DMPs) are now a standard part of grant proposals for most funding agencies.  DMPs describe the data you expect to acquire or generate during the course of a research project. Details include how you will manage, describe, analyze, and store the data, and what mechanisms you will use to share and preserve your data.

You may have already considered some or all of these issues but writing them down helps formalize the process, identify weaknesses in the plan, and provides a record of what you intend(ed) to do.  Use a Data Management Planning Tool such as DMPTool to create, review, and share data management plans that meet institutional and funder requirements.

Why Manage Your Data

  • Save time. Understanding your data needs and planning ahead will save you time and resources. By planning ahead you can make you data archive-ready, and with proper back-ups, you can help ensure that your data doesn't get lost due to machine error, theft, or a natural disaster.
  • Increase your research impact. Publications and data that are openly shared are cited more often. Supporting data archiving architecture and allowing others to re-use it can  demonstrate an impressive return on investment.
  • Simplify your research workflow. With everyone on the same page, you can focus more on working with your data than trying to find the right data. 
  • Preserve your data. Many data sets are unique and can only be collected once. By preserving your data you not only allow others to use it into perpetuity, you are saving an irreplaceable snapshot into our world and universe.
  • Increase your research efficiency. With proper data management, you'll be able to quickly understand and locate the data you've collected. This also means any collaborators or future users of your data will be able to find and understand your data -- increasing the potential uses of your data set and your data citations!
  • Meet funder requirements. Many funders have established data planning and sharing requirements, and as the benefits of data management become more evident, other funders are following suit.
  • Meet journal requirements. Increasingly, journals are enacting policies that require researchers to share and make accessible the data underlying a publication.
  • Facilitate new discoveries. Your data will have unknown uses in the future, and by sharing your findings you can ensure that others will be able to build off of your work in new and exciting ways.
  • Support Open Access. Show your support for Open Access by sharing your data -- and all the products of your research, from software to code to your publications. Learn more about Open Data and the Open Access Movements.

Data Management Plan Elements

Data Description: What data will be collected?  What's the scope and scale of the data?  Who do you expect the audience will be?  Are there other existing data that are relevant to what you are collecting?  This may help you decide where you want to archive it. 
Access and Sharing: How are you planning on archiving and sharing your data?  Why did you choose this method?  What terms of use do you have, if any?
Metadata: What types of metadata will be produced to support the data?  What metadata standards will be used? 
Intellectual Property Rights: Who will own the rights to the data and other information produced by the project? Will any copyrighted materials be used?  How will permission be obtained to use and disseminate the data?  Will these rights be transferred to another organization for distribution and archiving?
Ethics and Privacy: How is informed consent being handled and how is privacy being protected?
Format: What format(s) will you use for the submission, distribution, and preservation?  Preservation formats should be platform-independent and non-proprietary so that data will be reusable in the future.
Archiving and Preservation: What procedures will you use to ensure long-term archiving and preservation of your data?  What are the budget costs of preparing data and documentation?
Storage and Backup: Where and how will you store your data to ensure their safety (several copies are recommended)?  How will data be managed during the project? Include information about version control and file-naming conventions.  

*The above elements are an adaptation of the elements developed by the Inter-University Consortium for Political and Social Research (ICPSR) as part of their Framework for Creating a Data Management Plan


DMPToolThe DMPTool helps researchers create, review, and share data management plans in order to meet institutional and funding agency requirements. Researchers are increasingly required to engage in a range of data management activities to comply with institutional policies, or as a precondition for publication or grant funding.

The DMP Tool provides customized templates for various grants that aid researchers in creating effective data management plans, and save researchers valuable time. This tool also provides samples of public DMPs that are shared by their authors for others to use as models.

This video provides quick overview of the features of the easy to use DMPTool.  You can also use this self-help guide or schedule a consultation with a UCI librarian for additional support. For additional information, please contact the UCI Libraries' Digital Scholarship Services (DSS) department at

Data Management Checklist

  1. Always keep original data
  2. Back up regularly (automate this if at all possible)
  3. Document your data thoroughly (metadata, data dictionary)
  4. Name and organize files according to a schema
  5. Use version control
  6. Secure the data appropriately
  7. Cite any secondary data you use
  8. Consider your long-term plan
    1. What will you keep, for how long, where, and who will pay for it?
    2. What kinds of reuse or sharing will be allowed? In what timeframe?