What is Sensitive Data?
Sensitive data may contain information that should remain confidential in order to protect an individuals privacy, intellectual property, or an organization. Before depositing your data, it should be de-identified or anonymized to protect confidentiality or, if appropriate, intellectual property rights.
The Department of Health and Human Services provides detailed information about the de-identification of protected health information in their guide.
Including Statements About Sensitive Data in DMPs
If your research will produce sensitive data, you need to address this in you data management plan. You must not release any data that contains confidential or proprietary information. Data must be properly de-identified or anonymized prior to sharing.
The Office of Research and Graduate Studies has approved a statement regarding the sharing of confidential and proprietary information:
USU agrees with the principles that "data should be made as widely and freely available as possible while safeguarding the privacy of participants, and protecting confidential and proprietary data." In keeping with this guidance, USU follows policies and procedures which safeguard individuals, enhance national security, and appropriately protect confidential and proprietary information. Providing these protections may affect the timing or scope of data sharing. However, USU is committed to providing access to data related to its research outcomes as required under agency data sharing policies, generally no later than the time of final publication.
There are online resources to help you learn about sensitive data, direct and indirect identifiers, and how to prepare your data for sharing:
- Chapter 5 of the ICPSR's Guide to Social Science Data Preparation and Archiving
- Data De-identification: An Overview of Basic Terms, an overview by the Privacy Technical Assistance Center of the Department of Education. It includes many links to other resources.
- Chapman, A. D. and O. Grafton. 2008, Guide to Best Practices for Generalizing Primary Species-Occurrence Data, version 1.0. Copenhagen: Global Biodiversity Information Facility, 27 pp. ISBN:87-92020-06-2.
- Identify Data Sensitivity from DataOne
- Providing access to your data: Handling sensitive data Published on ESIP Commons. Provides overview of types of sensitive data (human, habitat, property, etc.) and discusses what should be considered when providing access to data.
- Johns Hopkins University Data Management Services maintains a list of Applications to Assist in De-identification of Human Subjects Research Data.
Contact us if you have questions or need help.