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Data Management Toolkit @ UNH

This toolkit provides information to help researchers develop data management plans and effectively manage their research data.

Why do I need a plan to manage my data?

Planning for your data management needs at the beginning of your research project will save you time and resources in the long run and ensure that your data will be compliant with standards in your field and usable in the future. A formal plan can be valuable to you and may be required by your funding agency.

DMPTool  and DMP Online are web-based tools to build and edit a customized plan according to select funder requirements (including the NSF).  DMPTool is a service provided by the University of California Curation Center (UC3) and DMP Online is a service provided by the UK's Digital Curation Centre (DCC). 

Links to the DMPTool.                                              

 

Data Management Plans: Recommended Components

What should be included in a data management plan? Although funding agencies such as the National Institutes of Health (NIH) and the National Science Foundation (NSF) may have specific requirements for plan content, there are fundamental data management principles that apply to most disciplines, formats, and projects. A data management plan will help you to manage your data for your own use, as well as to meet a funder requirement or enable data sharing in the future. Generally, a data management plan should contain the following components:

  • Description of the project: e.g., purpose of the research, organization(s) and staff involved
  • Description of the data to be collected: e.g., the nature and format of the data, how it will be collected, and overview of secondary data available on the topic
  • Standards to be applied for formats, metadata, etc.
  • Plans for short-term storage and data management: e.g., file formats, local storage and back up procedures, and security
  • Description of legal and ethical issues: e.g., intellectual property, confidentiality of study participants
  • Access policies and provisions: i.e., how will you make data available to others, any restrictions to to data reuse, etc.
  • Provisions for long-term archiving and preservation: e.g., in a data archive
  • Assigned data management responsibilities: i.e., which persons will actually be responsible for ensuring data management; how will compliance with this plan be monitored and ensured over time?

Data Management Plan Checklist

When developing your Data Management Plan, consider the following questions:

  1. How will the data be produced? Will it be reproducible? What would happen if it got lost or became unusable later?
  2. How much data will it be, and at what growth rate? How often will it change?
  3. Who will use ithe data now, and who might use it in the future?
  4. Who controls it or owns the data?
  5. What versions(s) of the data will be retained and for how long? e.g. 3-5 years, 10-20 years, permanently
  6. Are there tools or software needed to create/process/visualize the data?
  7. Are there any special privacy or security requirements? e.g., personal data, high-security data
  8. Are there any sharing requirements? e.g., funder data sharing policy
  9. Are there any other funder requirements? e.g., data management plan in proposal
  10. Is there good project and data documentation?
  11. What directory and file naming convention will be used?
  12. What project and data identifiers will be assigned?
  13. What file formats will be used? Are these formats stable?
  14. What is the storage and backup strategy?
  15. When and where will I publish the results from the data?
  16. When and where will I share the data with others?
  17. Who in the research group will be responsible for data management?

More about Data Management Planning

The resources below serve as good general models for any project (even though these may have been created for particular programs or funders):