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Data sharing

Learn the what, when, where, and how of data sharing.

What to share

Funders and publishers will provide some guidance on what data to share in order to meet their policies. For example, publishers typically recommend that you share all the data supporting the publication, or all the data necessary to replicate the research presented in the publication.

You may be considering other reasons to share your data, such as whether the data are vulnerable or historically significant. Such data make excellent candidates for preservation and sharing.

Ask yourself these questions

Ask yourself these questions before sharing your research data:

  • Are your data under any third-party agreements, licenses, or copyrights that restrict your ability to share?
    • Make sure you understand what the licenses or agreements do and do not allow you to do with the data, including data obtained from other researchers.
  • Are there intellectual property rights to be considered?
  • Does your data include anything the university has classified as high risk?
    • You should carefully evaluate whether the university allows you to share your data or requires that you take certain actions (like aggregating or anonymizing your data) before you can share. 
    • Check that your preferred repository is approved for data with your risk classification.
    Are there patient or other privacy issues? 
    • Check with your IRB and make sure you have the proper consents from study participants.
    • See more about working with sensitive data.
    • Consider whether your data should be aggregated, anonymized, or de-identified.
  • Does your data contain other types of sensitive information, like the location of endangered species?


Data in the categories above may not be openly shareable. Most funder and publisher policies exempt data that needs to be restricted for valid reasons, including cases like those mentioned above. You may need to provide justifcations to your funder or publisher for the data you are unable to share.

Data Best Practices

Data best practices and case studies

How to use best practices for managing your research data, along with case studies and examples to help you use these techniques.

Screenshot of Data Best Practices and Case Studies guide