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Data Management: Building a Data Management Plan

Checklist

Contextual Information

Contextual information is useful for others to understand your data. For example, readme files are a useful to communicate ownership, licensing, data explanations, related publications or datasets, data collection methods, etc.

Cornell University Library maintains a useful readme.txt template that can get you started. If the linked version is unavailable, you can use the attached version.

Data Curation

Data curation is a broad term that encompasses the creation, integration, organization, and preservation of data. It primarily involves the metadata (the information about your data) for your project rather than the datasets themselves. Good data curation is absolutely necessary to ensure that your data can be easily used by others who did not participate in the initial data creation process.

Some best practices of data curation include:

  • Adhering to standard file and folder naming conventions
  • Using non-proprietary file formats
  • Developing and implementing a clear back-up plan for your data
  • Providing context for your data within the metadata--what do your data labels mean?  What do your file names mean?

Most repositories and/or disciplines have standards and guidelines for data curation and metadata.  Check with your data repository or funding agency to find out their standards.  If you have questions, contact lib-data@olemiss.edu.

Privacy Concerns with Open Data

If your data contain identifiable information about human subjects, making that data freely available is more complicated.  If your data include such information, consult your discipline standards and/or funding agency requirements for guidance.  

General best practice in this situation is to include a statement outlining the terms and conditions of future access to the data in your data management plan.  

If practical, de-identification or anonymization may allow the data to be shared without compromising the privacy of the human subjects. If anonymization is impractical, datasets may be stored in a repository with restricted access.

Copyright of Data

In most circumstances, the University of Mississippi copyright policy gives researchers the intellectual property rights to the scholarship they produce. However, data are considered "facts" and are thus uncopyrightable, meaning they can be shared freely.  If your project arranges data in a way that adds value to the "facts", or if your data are in the form of software, the data may be eligible for copyright protection.

Note that the University Libraries are not legal experts and seek only to provide information about standard practices.  For legal advice concerning copyright issues, please consult the Office of General Counsel.