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Slides for a workshop conducted February 26 at Ludwig-Maximilians-Universität München. ## Abstract > In this workshop, we will try to tackle questions about privacy in the age of big and open data. Why should we even share our data? For what kind of research data do we need to maintain privacy? What is personally identifiable information and why is not sufficient to omit it to make data truly anonymous? How do we assess the risks of re-identification? How do we maintain our participants' anonymity, when we need to stay in touch with them online? What novel risks are engendered by the massive trail of data we all leave on the web? How do we anonymise already collected data by binning, fuzzing, and omitting? We will also discuss novel technological solutions that can permit us to share data openly: synthetic data generation, scientific use files, or differential privacy algorithms. The workshop consists of some theoretical input, but will also focus on practical exercises. Ideally, participants bring their own laptop with a current R installation. Furthermore, participants can send in questions or typical scenarios from their own research fields in advance.
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