Tools

This guide addresses qualitative data anonymisation from a theoretical, legal and practical perspective. After defining qualitative data anonymisation and addressing some common forms of resistance when it comes to anonymising such data, this guide presents the main anonymisation techniques. It a...

In the social sciences, requirements from funders and journals to make data available often present difficulties for researchers because of data protection issues. Anonymisation is a good solution for addressing the challenges of personal and sensitive data. This FORS Guide provides some practica...

This webinar gives an introduction to the key principles of qualitative data anonymization and guides researchers through the different techniques for anonymising their data, as well as file handling procedures. It also addressed some common concerns expressed by researchers, and how to possibly...

This webinar provides key concepts on anonymization in social science research to help researchers to develop an appropriate strategy, and to provide the main techniques for anonymising your quantitative data.

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 conf...

NSD's internal data processing platform.

This STATA do-file contains commands that proved useful for data checks. This by no means indicates that all necessary checks are part of this Do-File. It opens data from a SIP; saves to AIP; their quality and anonymisation checks are done; after checking the DIP is generated including long-term...

Amnesia is a flexible data anonymization tool that transforms relational and transactional databases to dataset where formal privacy guaranties hold. Amnesia transforms original data to provide k-anonymity and km-anonymity: the original data are transformed by generalizing (i.e., replacing one va...

Drawing on the Swiss context, this Guide illustrates key considerations in crafting a coherent anonymization strategy that is compliant with legal requirements and ethical norms. It shows how to strike the right balance between anonymization and other data protection measures, namely informed con...

This webpage from CSDA is an example of the guidance that an archive can develop to help data producers with data management. Topics covered are: Data file structure, Variables, Variable values and coding, Missing values, Data entry and data file integrity, Anonymisation, Weighting, Data file doc...