The OpenDP team is delighted to announce the release of OpenDP Library 0.6!
The OpenDP Library is a modular collection of algorithms for building privacy-preserving applications, with an extensible approach to tracking privacy, and a vetted implementation. It is available as binaries for Python on PyPI, for Rust on crates.io, or in source form on GitHub.
The OpenDP team is delighted (if a bit tardy) to announce the release of OpenDP Library 0.5!
This release is packed with enhancements to make the OpenDP Library more versatile and improve its robustness. The changes cover multiple aspects of the library, broadening the kinds of computations that can be performed, and making development more streamlined. ... Read more about OpenDP Library v0.5 Overview
We're pleased to release version 0.4 of the OpenDP Library. Highlights include several new measurements and transformations, improved floating point handling, and general code cleanup. The full list of changes can be...
We are excited to announce the launch of the newly designed OpenDP website. We hope you find the website content informative and a valuable resource for differential privacy. Most importantly, we look forward to having you become a part of the OpenDP Community.
As we draw to the close of an unusual year marked by the pandemic and the most difficult times it brought to us and our loved ones, the OpenDP team would like to extend our best wishes to you and your family this holiday season. Since our Community Meeting in May, we have been hard at work on starting to materialize the vision that we discussed. We would like to share with you our progress and our outlook for the coming year.
We are writing to share some interesting discussions between the OpenDP team and Red Hat.
James Honaker and Mercè Crosas discussed the importance of data sharing and privacy preservation, in both scientific and computer technology domains, with Sherard Griffin, Director at Red Hat in the AI Center of Excellence, in Red Hat's Regional Quarterly newsletter:
The OpenDP project seeks to hire 1-2 scientists to work with faculty directors Gary King and Salil Vadhan and the OpenDP Community to formulate and advance the scientific goals of OpenDP and solve research problems that are needed for its success. Candidates should have a graduate-level degree (preferably a PhD), familiarity with differential privacy, and one or both of the following:... Read more about OpenDP Hiring Scientific Staff
We are grateful to the many thought leaders who have agreed to serve on the inaugural OpenDP Advisory Board. The first Advisory Board meeting was held as part of the first OpenDP Community Meeting, on May 15th, 2020. The discussion covered a wide range of topics, including governance, use cases, community role / mission and finances, as detailed in their report, which offers a wealth of insightful advice for OpenDP.... Read more about OpenDP Advisory Board Report
In September 2019, Harvard’s Institute for Quantitative Social Science announced a large-scale collaboration with Microsoft to develop open source tools for differential privacy, work that is now part of the broader OpenDP community effort. We are thrilled to report on the progress our collaboration has made, and we write today to report on two lines of substantial progress.... Read more about Update on the OpenDP-Microsoft Collaboration
Like many others, we on the OpenDP team are angered and saddened by the murders of Ahmaud Arbery, Rayshard Brooks, George Floyd, Breonna Taylor, and many Black Americans before them. We spent last Wednesday participating in #ShutDownSTEM, reflecting on the systemic racism in academia and the tech industry and how we can work towards eliminating it.
The following news from the Social Science One project may be of interest to the OpenDP Community. If you have news you would like to share with the community, please feel free to use this mailing list firstname.lastname@example.org
-------------------------------------------------------------------------------------------- We've updated the Social Science One - Facebook "URLs dataset". It now has 17 trillion cell values with social media data from 46 countries. https://t.co/XYcvxhOMPl We believe it to be the largest differentially private corporate dataset ever released to academic researchers.
One of OpenDP use cases is the integration of OpenDP tools with public data repositories to release differentially private statistics of sensitive data hosted in the repository. Public data repositories have become ubiquitous in research and are a key part of the research lifecycle. Funders increasingly require sharing the research data associated with a funded project in a data repository when the project ends; journals increasingly require publishing the data associated with a scholarly article in a supported data repository;... Read more about Dataverse Community Meeting and Integration of OpenDP with Data Repositories
THANK YOU for your wonderful participation in the first OpenDP Community Meeting last week!
In spite of the online format with over 400 registrants, we felt a strong sense of connection and shared mission being built. We came away energized and inspired by the ideas and feedback you all provided. For those of you who could not attend, you can find readings, presentation videos, and slides on... Read more about The OpenDP Community