PRESIDENT AND FELLOWS OF HARVARD COLLEGE

OpenDP is a community effort to build a trustworthy suite of open-source tools for enabling privacy-protective analysis of sensitive personal data, focused on a library of algorithms for generating differentially private statistical releases. The target use cases for OpenDP are to enable government, industry, and academic institutions to safely and confidently share sensitive data to support scientifically oriented research and exploration in the public interest. We aim for OpenDP to flexibly grow with the rapidly advancing science of differential privacy, and be a pathway to bring the newest algorithmic developments to a wide array of practitioners... We began this project in a (still ongoing) partnership with Microsoft developing a differentially private data curator application called SmartNoise. Building on this collaboration, we are now establishing a broader community around OpenDP with stakeholders and contributors from across academia, industry, and government. Together, we..