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Bay Area Open Science Group - Developing open source air quality datasets for public health policy action

This month we are joined by Ayako Kawano, a PhD candidate in the Emmett Interdisciplinary Program in Environment and Resources at Stanford. Ayako’s research examines the impact of air pollution on population health and climate change in low- and middle-income countries using remote sensing data and machine learning methods. Ayako recently won the Stanford University Libraries Data Sharing Prize for her work publishing a long-term dataset of fine particulate matter concentrations in India, which has been used to inform public health programs and policy as well as used in further research projects.

The Bay Area Open Science Group is a growing community for Bay Area academics and researchers interested in incorporating open science into their research, teaching, and learning. Targeting students, faculty, and staff at UCSF, Berkeley, and Stanford, the goal of the community is to increase awareness of and engagement with all things open science, including open access articles, open research data, open source software, and open educational resources. Through this work the group hopes to connect researchers with tools they can use to make the products and process of science more equitable and reproducible.

UCSF welcomes all participants to our events. If you need a reasonable accommodation to participate in this event because of a disability, please contact Ariel Deardorff at ariel.deardorff@ucsf.edu as soon as possible.

Register for this event via Zoom

Related LibGuide: Reproducible Data Management by Ariel Deardorff

Date:: Tuesday, Feb 24 2026
Time:: 2:00pm - 3:00pm
Time Zone:: Pacific Time - US & Canada (change)
Campus:: Online
Categories:: Data Science Scholarly Communication

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Event Organizer

Ariel Deardorff

Director of Data Science and Open Scholarship

ariel.deardorff@ucsf.edu