De-identifying qualitative data poses unique challenges given their structure and contextual richness. As the sharing of qualitative data is becoming more common, reliably de-identifying such data is crucial because participants in qualitative research projects commonly receive assurances of confidentiality. This webinar brings together speakers from three different groups working on de-identifying – and sharing – qualitative data to talk about their methods and tools.
Slides:
Qualitative Data Sharing (QuaDS) Software: Performance and User Satisfaction Data: [ Ссылка ]
ANONYMISATION OF QUALITATIVE DATA IN FSD: [ Ссылка ]
Anonymizing qualitative text data - the approach of the Research Data Center Qualiservice: [ Ссылка ]
