Assessing Community Well-being through Open Data and Social Media

Example report page for International District neighborhood

Example report page for International District neighborhood

Project Lead: Shelly Farnham, Third Place Technologies

DSSG Fellows: Jordan Bates, Ryan Burns, Jenny Ho, Yue Zhou

ALVA Students: Avery Glass, Jennifer Nino

eScience Data Scientist Mentors: Bernease Herman, Bill Howe

Our DSSG Fellows and ALVA students paired with Third Place Technologies to create neighborhood community report pages in the context of a hyperlocal, crowd-sourced community network. The objective was to help neighborhood communities better understand the factors that impact community well-being, and how they as a neighborhood compare with other neighborhoods on these factors. This helps them set the agenda for what to prioritize in promoting their well-being. A key aspect of this project was to explore novel ways to leverage diverse social media and open data sources to dynamically asses community-level well-being, in order to a) enable early identification of emerging social issues warranting a collective response, and to b) automatically identify and recommend the local community hubs best positioned to coordinate a community response.

Click here to read the project’s full summary.

Open Sidewalk Graph for Accessible Trip Planning

Graphic of sidewalk data in downtown Seattle

Graphic of sidewalk data in downtown Seattle

Project Leads: Nick Bolten, Anat Caspi

DSSG Fellows: Amir Amini, Yun Hao, Vaishnavi Ravichandran, Andre Stephens

ALVA Students: Nick Krasnoselsky, Doris Layman

eScience Data Scientist Mentors: Anthony Arendt, Jake Vanderplas

This project is an extension of the “Hackcessible” project that was awarded top prize in this year’s “HackTheCommute” event in Seattle. Hackcessible has built an application that helps people with mobility challenges to navigate the streets of Seattle based on sidewalk characteristics and the presence of curb ramps. Expanding on these ideas, the DSSG team worked to utilize city sidewalk and street data to provide stakeholders with routing information, similar to what is currently provided by Google Maps, but that considers issues of accessibility. The goal of the effort was to provide rapid and convenient routing that avoids steep hills, uncrossable intersections, stairs or construction. The work was carried out in partnership with Dr. Anat Caspi of the Taskar Center for Accessible Technology at the University of Washington, and with various stakeholders with the City of Seattle and the Washington State Department of Transportation.

Click here to read the project’s full summary.

Predictors of Permanent Housing for Homeless Families

Program trajectories are a series of programs that a family encounters during a contiguous episode of homelessness

Program trajectories are a series of programs that a family encounters during a contiguous episode of homelessness

Project Leads: Neil Roche and Anjana Sundaram, The Bill and Melinda Gates Foundation

DSSG Fellows: Joan Wang, Jason Portenoy, Fabliha Ibnat, Chris Suberlak

ALVA Students: Cameron Holt, Xilalit Sanchez

eScience Data Scientist Mentors: Ariel Rokem, Bryna Hazelton

The Bill and Melinda Gates Foundation, together with Building Changes have partnered with King, Pierce and Snohomish counties to make homelessness in these counties rare, brief and one-time. The goal of this project was to take part in this multi-stakeholder collaboration, and to analyze data about enrollments of homeless families in these counties in programs serving the homeless population, to identify factors that predicted whether families would succeed in finding permanent housing, and to investigate the ways families transition between different programs and different episodes of homelessness.

Click here to read the project’s full summary.

Rerouting Solutions and Expensive Ride Analysis for King County Paratransit

Weekly time series of out-of-service buses

Weekly time series of out-of-service buses

Project Lead: Dr. Anat Caspi, Taskar Center for Accessible Technology

DSSG Fellows: Rohan Aras, Frank Fineis, Kristen Garofali, Kivan Polimis

eScience Data Scientists: Joseph Hellerstein and Valentina Staneva

DREU Fellow: Emily Andrulis, Cornell College Weekly

The Paratransit team collaborated with King County Metro to improve operations of the Paratransit service, which is an on-demand public transportation program that provides door-to-door rides for people with limited ability who are unable to use traditional fixed route services. Currently, King County Metro paratransit trips cost approximately ten times as much as an equivalent trip using a fixed-route service, so the team concentrated their efforts on identifying costly routes, providing cost-driven recommendations for rescheduling broken buses, and better predicting service usage hours over quaterly periods. The team analyzed history data and observed rides whose cost per boarding was over $100, providing King County Metro with a method to update predictions of usage hours customized for each day of the week and a web app which provides cost comparison for the different options of handling a broken bus event: reschedule clients on an existing route, send a new bus, or serve them with a taxi. These tools aim to help the Paratransit operations better plan resources over longer periods of time and help dispatchers make informed decisions in case of emergency.

Click here to read the project’s full summary.