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Data Management

Data Management Guide for Faculty, Researchers, and Students.

Generic Data Management Plan Elements

Each funder will have different requirements, but many follow the pattern as follows:

1. Types of data produced

Provide a brief description of the data being collected.  

  • What data will be generated in the research?
  • What data types will you be creating or capturing?
  • How will you capture or create the data?
  • If you will be using existing data, state that fact and include where you got it.
  • What is the relationship between the data you are collecting and the existing data?

2.  Data and metadata standards

Explain how you will describe your data in a way so that others can make use of it.  Describe the file structure, the variables, etc.

  • Which file formats will you use for your data, and why?
  • What form will the metadata describing/documenting your data take?
  • What contextual details (metadata) are needed to make the data you capture or collect meaningful?
  • How will you create or capture these details?
  • Which metadata standards will you use and why have you chosen them? (e.g. accepted domain-local standards, widespread usage)

3.  Policies for access and sharing

Describe how and when your data will be made available once your project is completed.

  • How will you make the data available? (Include resources needed to make the data available: equipment, systems, expertise, etc.)
  • When will you make the data available?
  • What is the process for gaining access to the data? Will there be a fee to gain access?
  • How long will the original data collector/creator/principal investigator retain the right to use the data before making them available for wider distribution?
  • Do you need embargo periods for political/commercial/patent reasons? If so, give details.
  • Are there ethical and privacy issues? If so, how will these be resolved?
  • Can you demonstrate your compliance with IRB Protocol?
  • Who will hold the intellectual property rights to the data and how might this affect data access? (Consider benefits of creating permanent identifiers for easy citation of datasets.)

4.  Policies for re-use, redistribution

Identify your plans for allowing for reuse of your data.  If you plan to restrict access, reuse, or redistribution, explain how you will communicate those restrictions.

  • Will any permission restrictions need to be placed on the data?
  • Which bodies/groups are likely to be interested in the data?
  • What and who are the intended or foreseeable uses / users of the data?

5.  Plans for archiving & preservation

This is where you layout your plans for the long-term storage and preservation of your data.

  • What is the long-term strategy for maintaining, curating and archiving the data?
  • Which archive/repository/database have you identified as a place to deposit data?
  • What procedures does your intended long-term data storage facility have in place for preservation and backup?
  • How long will/should data be kept beyond the life of the project?
  • What data will be preserved for the long-term?
  • What transformations will be necessary to prepare data for preservation/data sharing?
  • What metadata/documentation will be submitted alongside the data or created on deposit/ transformation in order to make the data reusable?
  • What related information will be deposited?