This webinar is intended to provide an accessible and practical introduction to the theory and concepts behind data anonymization, looking specifically at anonymization of survey microdata. Topics covered will include an overview of identifiers and quasi-identifiers, an introduction to k-anonymity, a look at some cases where k-anonymity breaks down, and anonymization hierarchies. The presenter will describe a method to assess a survey dataset for anonymization using standard statistical software. Much of the academic material looking at data anonymization is quite abstract and aimed at computer scientists, while material aimed at data curators does not always consider recent developments. This webinar is intended to help bridge the gap.
About the Presenter:
Kristi Thompson has been the research data management librarian at Western University since 2019, and previously held positions as data librarian at the University of Windsor and as a data specialist at Princeton University. Her involvement with Portage includes participation on the Federated Research Data Repository and Dataverse North working groups. She has a computer science background and has published on topics ranging from international data sources to aboriginal sports practices.
This webinar will be presented in English and recorded. Engagement during the webinar in both official languages is welcomed. Previous webinar recordings are available on the CARL YouTube Channel. Links to the recordings and slides can also be found on Portage Training Resources.