Anonymisation

Anomymisation of quantitative data

  • This may involve removing or aggregating variables
  • Aggregate or reduce the precision of a variable such as age or place of residence
  • Restrict the upper or lower ranges of a continuous variable to hide outliers if the values for certain individuals are unusual or atypical within the wider group researched

See also: https://www.cessda.eu/Training/Training-Resources/Library/Data-Management-Expert-Guide/5.-Protect/Anonymisation

Anonymisation of qualitative data

  • Plan anonymisation at the time of transcription or initial write-up
  • Use pseudonyms that are consistent within the research team and throughout the project
  • Use 'search and replace' techniques carefully so that unintended changes are not made, and misspelt words are not missed
  • Identify replacements in text clearly: [brackets] or using XML tags such as word to be anonymised
  • Create an anonymisation log of all replacements, aggregations or removals made and store such a log securely and separately from the anonymised data files

See also: https://www.cessda.eu/Training/Training-Resources/Library/Data-Management-Expert-Guide/5.-Protect/Anonymisation