Linking Big Data and Surveys in Practice: Solutions for Respondents Privacy Protection
|Convenor:||Professor Rainer Schnell|
|Affiliation:||City University London|
Linking survey data to big data and administrative data is an increasingly popular research strategy in official statistics as well as in social and medical sciences. In research settings using micro data, privacy of respondents is of utmost importance. Examples are geocoded services or respondent addresses, where the actual locations have to be protected by statistical measures or mathematical transformations (geomasking). Similar problems result by the availability of mobility tracks produced by cars, phones or laptops. The problems are even more severe with biomarkers or genetic data. Finally, linking different databases and/or surveys is possible in practice only if the privacy of the respondents can be protected. This requires in many cases the use of Privacy Preserving Record Linkage Techniques.
During the last 10 years, the privacy problems created by the increasing availability of big data and survey data has given rise to many different mathematical and statistical techniques to preserve the privacy of the respondents. The goal of the session is the presentation of these techniques to a broader audience. Tutorials as well as recent developments are welcome.
We invite presentations on:
1. Analyzing individual geographical data without revealing locations
2. Protecting anonymity in the analysis of mobility profiles
3. Privacy Preserving Record Linkage
4. Privacy of biomarkers and genetic data.
Research on informed consent will not be covered in this session. Statistical disclose control is also considered as a topic for other sessions.