Anonymization minimizes the risk data processing stages and can also enable data sharing and reuse. At the same time, full data anonymization is often difficult, especially when working with qualitative and context-sensitive data such as interviews, audio and video recordings and images.
During the course, participants will learn about the importance of data anonymization in research, core definitions and concepts relating to anonymization and challenges facing especially qualitative and context-sensitive data.
We will also present practical aspects of data minimization, including strategies for pseudonymizing and anonymizing interviews, surveys, and different types of observational data. There will be also a possibility of asking questions relating to individual dataset’s anonymization.
Take aways
This course is aimed at PhD candidates, postdocs and other early career researchers as well as senior researchers and technical and administrative staff who guide researchers in questions related to data management and sharing. The goal is for participants to gain a better understanding of what data pseudonymization and anonymization is and to become familiar with few basic strategies for pseudonymization and anonymization of personal data.
Instructor
Agata Bochynska is a researcher and a research librarian focusing on implementing open research and reproducibility practices across disciplines. Agata's academic background is in psychology and linguistics and her current interest is in meta-scientific assessments and evaluating implementation of open research. She works in the Open Research team at the University of Oslo Library and is the project coordinator of QualiFAIR.
Torgeir Christiansen is a senior engineer and the leader of the Teaching Learning Video lab (TLVlab). He works with IT solutions and support and is one of the faculty experts in data protection and data privacy. Torgeir has extensive experience as a course holder in GDPR for students and researchers at the Faculty of Educational Sciences.