This project is a part of the Data Science Working Group at Code for San Francisco. Other DSWG projects can be found at the main GitHub repo.
This project attempts to model and acquire data from SF OpenData - and other sources - to predict the relative risk of fire in San Francisco’s buildings and public spaces.
The mapping software will allow the user to type in an address and see fire-related risks and incidences around their area, as well as provide recommendations by fire safety experts in cases where there may be a high enough score to warrant preventive actions. This project is modeled after Data Science for Social Good's (DSSG) Firebird Project in Atlanta, GA. Consultation is occasionally provided by members of the DSSG and former members of the Atlanta project.
1) data scientists 2) data analysts 3) data visualizers 4) researchers and journalists (find trends and data related to fire incidents in the city) 5) product and project managers
Our workflow chart is here: SF Fire Risk Workflow
SF Fire Risk Attribute Sheet SF Fire Risk Predictive Model Attribute Sheet (Always adding more!)
Name | Slack Handle | Role | Website |
---|---|---|---|
Ryan Tanaka | @ryangtanaka | Product Manager, Team Lead | http://product.ryangtanka.com |
Kel Yip | @yamariva2000 | Data Scientist, Technical Lead | |
Seward Lee | @sewardlee337 | Data Scientist | http://www.sewardlee.com |
Kenny Durell | @kennyd | Data Scientist | |
Sam Williams | @swilliams2099 | Research, Outreach | |
Kevin Stahler | @stahlerk | Data Scientist | |
Yuzhe Chen | @yzxchn | Data Scientist | |
Chris Quiambao | @ccquiambao | Data Scientist | https://github.com/ccquiambao |
Hannah Gorman | @hannahrosey | Data Scientist, Visualization |
#datasci-firerisk