A community dedicated to truthful, reliable data analysis and decision-making gathered together on May 31, 2024, for a one-day workshop that showcased veridical (truthful) data science (VDS). The Inaugural Berkeley-Stanford Workshop on Veridical Data Science was jointly hosted by the Berkeley Institute for Data Science (BIDS), the Stanford Data Science Center for Open and REproducible Science (SDS-CORES), and the UC Berkeley Department of Statistics. It featured four keynotes, ten invited speakers, and five lightning talks. The sold-out event drew statisticians, data scientists, graduate students, and early career researchers for insightful discussions and networking, highlighting the growing interest in veridical data science. Watch the recordings from the event here!
More about Veridical Data Science (VDS)
Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making, a book from MIT Press, is an essential source for producing trustworthy data-driven results, written by Bin Yu and Rebecca Barter. Excerpt from the Preface:
Data science is not simply a subfield of statistics or computer science. Instead, it is the integration of statistical and computational thinking into real-world domain problems in science, technology, and beyond. Since data science projects are grounded in real-world problems, it is thus important that data scientists work side by side with domain scientists or experts to ensure that their data-driven results provide useful, ethical, and trustworthy solutions to the real-world domain problem.
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- Berkeley Institute for Data Science (BIDS) LinkedIn page & newsletter
- Stanford Data Science Center for Open and REproducible Science (SDS-CORES) LinkedIn page & newsletter
- UC Berkeley Department of Statistics LinkedIn page & website news
