The Data De-Identification Dilemma

Data de-identification refers to breaking the link between data and the individual with whom the data is initially associated. This requires removing or transforming personal identifiers. 

Data de-identification serves as an indispensable guardian of individuals’ privacy, ensuring legal and regulatory compliance, mitigating risks from data breaches, and enabling safe data use for research. If you are conducting Human Subject Research at GW, and plan to publish data on human subjects, you know you have to take careful steps to protect the confidentiality of study participants through data de-identification. 

Join us as the GW Privacy Office leads a discussion on how de-identification requirements differ significantly across privacy laws, such as FERPA, HIPAA and GDPR, because each law has its own definition of what constitutes "identifiable" data and its own standards for what must be removed to consider data de-identified.

To bridge the gap between policy and practice, research librarians from Libraries and Academic Innovation will provide guidance on tools for de-identifying your data, as well as best practices for navigating data repositories and sharing requirements, to ensure your research is both impactful and secure.