Workshop: Programmatic Data De-identification with R

This practical workshop, delivered by the UBC Library Research Data Management team, introduces programmatic approaches to de-identifying sensitive research data in R. Through hands-on exercises using a realistic survey dataset, participants will apply a structured workflow, from assessing privacy risks to exporting a shareable, de-identified dataset.

Participants will learn how to:

• Identify privacy risks in research data, including direct identifiers, dates, geographic variables, and free-text fields.
• Apply de-identification methods in R using dplyr, including removal, generalization, suppression, anonymization, and pseudonymization.
• Run quality assurance checks to confirm a dataset is sufficiently de-identified before sharing.
• Export a de-identified dataset and a data key file, and understand best practices for securely storing each.

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Note 1: Participants familiar with R and RStudio are welcome to follow along on their own workstations. If you are new to R, we recommend watching first to learn how R can be used for analysis and data de-identification, then practicing later with the resources introduced during the session.

Note 2: This workshop provides a practical introduction to programmatic data de-identification. Participants are encouraged to consult their institutional privacy, legal, or compliance experts for guidance on specific datasets.

Location: ONLINE

(A Zoom link will be sent to registrants 3 hours before the event starts.)