Skip to Main Content

Research Data Management: Sharing Your Research Data

This guide is a resource to help navigate common best practices and guidelines regarding data throughout your research project

Why Share your Research Data?

Benefits of data sharing to individual researchers and the research community:

  • promotes new discoveries
  • increases research impact
  • supports validation and replication
  • enhances collaboration
  • increases returns from public investments
  • reduces redundant research

Ethical Considerations

There are three primary areas that need to be addressed when producing sharable data:

  1. Privacy and confidentiality: Adhere to your institution's policy.
  2. Copyright and intellectual property (IP): Data is not copyrightable. Ensure that you have the appropriate permissions when using data that has multiple owners or copyright layers. Keep in mind that information documenting the context of data collection may be under copyright.
  3. Licensing: Data can be licensed. The manner in which you license your data can determine its ability to be consumed by other scholars. For example, the Creative Commons Zero License provides for very broad access.

If your data falls under any of the categories below there are additional considerations regarding sharing:

  • Rare, threatened, or endangered species
  • Cultural items returned to their country of origin
  • Native American and Native Hawaiian human remains and objects
  • Any research involving human subjects

DataONE. (n.d.). Sharing data: Legal and policy considerations. https://old.dataone.org/best-practices/sharing-data-legal-and-policy-considerations

Readings, Guidelines, and Recommendations for Data Sharing

Journal and Publisher Requirements

Journals and publishers may require data to be shared, or deposited within an open repository for access by readers. Review the journal's requirements (usually found within the author's instructions) for data sharing on their website.

How to Share Data

Research data can be shared in various ways:

  • Data Repository/Data Archive
  • Self-Preservation and dissemination
  • Submit data to a journal or publish a data paper