Privacy represents a broad variety of concerns — subjective, contextual, hard-to-define — that real people have about the flows of personal information. Location-based services provide a key example: a growing field that uses potentially sensitive data, where adoption has been held back by privacy concerns.
Translating these concerns (as well as corporate and legal liability) into technical artifacts — a process known generally as "privacy-by-design" — has proven difficult. How can we best convert lawyer speak into engineering speak? How can problems be elegantly anticipated early in the development process?
Drawing inspiration from Christopher Alexander and the success of software design patterns in improving communication about tried-and-true practices, we hope privacy patterns will:
- standardize language for privacy-preserving technologies
- document common solutions to privacy problems
- help LBS designers identify and address privacy concerns
We're currently compiling a first draft of some patterns to get things started, but our goal is for this to be a living document constructed by the community of engineers, designers, lawyers and regulators involved in this topic.
Nick Doty is a PhD student at the UC Berkeley, School of Information and works on privacy at the World Wide Web Consortium.
Mohit Gupta develops mobile software at Location Labs with a focus on building privacy into products.
Jeff Zych and Rowyn McDonald are Master's students at the School of Information and built this site!
If you're interested in privacy patterns — because you'd like to contribute your own content, support the project in some way or suggest an improvement — please contact us.