Developing Open Source Tools for Differential Privacy

OpenDP is a community effort to build trustworthy, open-source software tools for statistical analysis of sensitive private data. These tools, which we call OpenDP, will offer the rigorous protections of differential privacy for the individuals who may be represented in confidential data and statistically valid methods of analysis for researchers who study the data.

Learn More About Us

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Use Our Tools

Do you have data to share or an application that can benefit from differential privacy? We can help. 

Learn how to use OpenDP Tools

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Whatever your background, there are ways in which you can contribute to the OpenDP effort. 

Learn how to contribute

Join Us

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Core Team

The OpenDP team is continually growing! Currently we are accepting applications for our Scientific Staff and for the OpenDP Fellows Program. Please contact us if you are interested in joining us, even if we do not have a suitable job posting at the moment. 

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Please join our mailing list to get connected with the rest of the OpenDP Community, to stay abreast of our latest developments, and to find opportunities to contribute. 

Latest Blog Posts

Introducing OpenDP Library v0.5

Dear OpenDP Community,


The OpenDP team is delighted (if a bit tardy) to announce the release of OpenDP Library 0.5!

As a reminder, the OpenDP Library is a modular collection of algorithms for analyzing sensitive datasets, with a flexible and extensible approach to tracking privacy, and a vetted implementation. It can be used to build a wide range of data processing pipelines and privacy-preserving applications. The OpenDP Library is available as binaries for Python on PyPI, for Rust on, or in source form on GitHub.
... Read more about Introducing OpenDP Library v0.5

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