Data Bites – Introduction to Programmatic Data De-identification with R

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.