UW’s Data Science for Social Good Program Uses “Big Data” for an Array of Projects

By Henry Lemersal, San Diego Supercomputer Center Intern


At the University of Washington (UW) eScience Institute’s Data Science for Social Good (DSSG) program, it’s not just about the numbers. With support from the West Hub, the program hosts multiple projects analyzing data in order to tackle societal challenges each summer.

audience watching a presentation

The recent DSSG Learning and Doing Data for Good Conference was attended by students and professionals from across the nation sharing how they have applied data science to an array of important societal issues.


“This unique conference created a platform to highlight the work of student teams using their data science skills for socially impactful projects across a range of topics and partner organizations,” said Executive Director of UW’s eScience Institute Sarah Stone. “Students from different programs had the opportunity to network with each other as well as to meet data for good practitioners working in government, nonprofits, industry and academia.”


The conference was kicked off by a speech from Desmond Upton Patton, a professor from the University of Pennsylvania. Patton, who utilizes data to determine negative impacts of social media on youth of color and their communities, hopes that by studying the issues that plague such communities, he can get a better understanding of how to help or provide additional support channels.

3 people sitting and speaking into microphones

Project presentations at the conference included many student-led talks. One such talk discussed how “big data” was used to understand a livable wage and cost of living. Additional projects included creating tools to eliminate light pollution in astronomy photos while another focused on predicting thermal energy usage in the state of Alaska by various sources. All DSSG projects can be found here.


“DSSG is a magnet for students,” said UW professor and founding eScience Institute Director Ed Lazowska. “It gives them an opportunity to enhance their data science skills while addressing a socially valuable project of importance to a partner organization.”


Detection of Vote Dilution: New tools and methods for protecting voting rights was one of the projects presented at the September 2022 conference. The eight-person team developed tools to help detect racial gerrymandering and vote dilution. They engaged with stakeholders throughout development to ensure usability and accuracy, as well as to ensure that these analyses are easily accessible. The team consisted of the following: Project Leads: Matt Barreto (UCLA) and Loren Collingwood (University of New Mexico) Data Science Leads: Scott Henderson (University of Washington) and Spencer Wood (University of Washington) DSSG Fellows: Juandalyn Burke (University of Washington), Ari Decter-Frain (Cornell University), Hikari Murayama (UC Berkeley), Pratik Sachdeva (UC Berkeley)







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