Unmasking Data Disasters

Become a data detective and help us take a supposedly anonymous data set and reveal the identities of the people within it.

Data detectives trained
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Lesson overview

When collecting data about people, researchers don’t want to accidentally cause harm, or risk sharing too much information.

They try to reduce the amount of personal data in their data sets. By minimising personal data, they minimise the dangers.

But if it's not done properly, can this be undone? Is there a data disaster waiting to happen?

Objectives
  • Read and unmask the 'anonymised' job applications

  • Decode browsing history to find the secretive 'Stardust Streams'

  • Compare a medical dataset with 'open' data to identify patients

  • Run Python code to automate the re-identification process

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