Data Bites – Introduction to Manual Data De-identification

Workshop: Introduction to Manual Data De-identification

This practical workshop, delivered by the UBC Library Research Data Management team, is the second session in a four‑part series on de-identifying and preparing sensitive data for responsible research use and sharing. Building on the concepts introduced in the first session, this hands‑on workshop focuses on applied manual techniques for de-identifying datasets containing sensitive information.

Participants will learn how to:

- Apply core manual de-identification methods, including anonymization, pseudonymization, aggregation, masking, generalization, and local suppression, to protect participant privacy. - Work through a step-by-step de-identification workflow, addressing direct identifiers, dates, geographic data, and variables linkable to external sources. - Select the most appropriate de-identification method for each variable type based on sensitivity and analytical need. - Assess the anonymity of a finalized dataset using measures such as k-anonymity to evaluate whether it is sufficiently de-identified for sharing.

Note: This workshop provides a foundational introduction to manual data de-identification. Participants are encouraged to consult their institutional privacy, legal, or compliance experts for guidance on specific datasets.