Welcome to NYC School of Data — a community conference that demystifies the practices and policies around open data, technology, and service design. Hosted by BetaNYC at CUNY School of Law, this year’s conference concludes NYC’s Open Data Week 2026 and is the TENTH edition of both SoData and Open Data Week!
2026 is bigger than ever with 40+ sessions organized by NYC’s civic technology, data, and design community!
Day 1: the classic NYC School of Data conference, with programming across 12 rooms during 4 session blocks.
Day 2: NEW in 2026 – UnSchool of Data! The unconference agenda is created together on the day, with attendee pitches at the top of the day. Select sessions have been pre-seeded by BetaNYC to kick things off.
Our venue is accessible and content is all-ages friendly! If you have accessibility questions or needs, please email us at < [email protected] >.
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This program is an introduction to using image recognition AI in the context of urban planning or analyses of the urban environment. Images can be a rich source of information, but their use in academic or analytic studies has been limited, owing either to their size, their availability or a lack of awareness into how computers "read" them.
This session will focus on a set of storefront photography provided by a New York City-focused storefront database called Live XYZ, but any similar set of images, like from Google's Streetview for example, could be used as well.
Policy Analyst Alexander McQuilkin be presenting a project he undertook to understand gentrification in one Brooklyn neighborhood, borrowing an A/B signage classification index developed by a pair of CUNY anthropology and linguistic professors. Anyone interested in urban aesthetics and/or machine-learning should attend, and can expect to come away with new tools for analyzing images and ideas about how we can measure our urban environment. No coding experience necessary. Attendees can bring their laptops to interact with the AI tools live, or can just take notes and experiment with it later.
