
Data Bites – Introduction to Programmatic Data De-identification with R
Hands-on workshop from UBC Library to learn programmatic data de-identification workflows in R using a realistic survey dataset
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.
To participate fully, you will need to install the latest versions of R and RStudio on your computer before the workshop: Install R from https://cran.rstudio.com/ Install RStudio from https://rstudio.com/products/rstudio/download/#download
Note: 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.






