Privacy-Preserving Data Analysis
The general goal of research into privacy-preserving data analysis is to develop techniques that allow to get the best utility out of a dataset without violating the privacy of the individuals represented in it. This includes finding secure ways of providing public access to private datasets, securely decentralising services that rely on private data from individuals, enabling joint analysis on private data held by several organisations, and securely outsourcing computations on private data.
One of the UK's foremost computer scientists, Peter Buneman FRS MBE works primarily on database systems and programming languages. He pioneered research on managing semi-structured data, as well as on data provenance, annotations, and digital curation. His work has had widespread application, including in bioinformatics and computational biology.