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Graduate Campus

Publishing personal and sensitive data


  • Postdocs: Please use our registration form.
  • PhD or Academic Associate: Please send us an email to register.

While it is generally recommended that all data underlying a scientific article is published, researchers working with personal and/or sensitive data often refrain from doing so because of ethical or legal reasons or because they do not know how. However, even sensitive data can be shared if individuals have been de-identified (with anonymization or pseudonymization techniques) and if study participants have agreed to the sharing of their (de-identified) data. In this course, participants will require the necessary skill set to address legal and ethical considerations to eventually publish personal or sensitive data. Participants will learn about copyright, licenses, data protection, disclosure risk and data utility and will practice reproducible anonymisation techniques in hands-on sessions (for qualitative and quantitative data). The course takes place in two half-days with online learning components before each course day.

Course objectives

At the end of the course, participants are able to:

•    … understand the principles of data protection and copyright
•    … distinguish and select appropriately between the different types of licenses to publish their work
•    … characterize sensitive/personal data and practice the sharing of such data in some cases
•    … describe the difference between pseudonymization vs anonymization
•    … understand the trade-off between disclosure risk and data utility
•    … practice some easy techniques in R (e.g. re-coding, suppression, aggregation)
•    … apply methods for statistical disclosure control

Instructors Dr. Melanie Röthlisberger & Dr. Eva Furrer & Reto Gerber
University Library UZH (UB) & Center for Reproducible Science (CRS), University of Zurich
Target participants This course is aimed at all researchers at UZH who work with sensitive or personal data. Participants working with quantitative data are required to have some prior working knowledge of R.

15 January 2024 13:00 - 16:30h

29 January 2024 13:00 - 16:30h 

Location RAA-E-30