Data for Good Exchange, 2017

The Data for Good Exchange conference focused on applications of data science that benefit the public. This is strongly aligned with the mission of SUDS. Our objective for attending the conference was to learn more about how practitioners, academics, and others are using data analytics in creative ways to address public policy concerns.
Ada Tso, Ben Simmons, and Chris Worley at the Data for Good Exchange, 2017
Ada Tso, Ben Simmons, and Chris Worley at the Data for Good Exchange, 2017
The conference was attended by a cross-section of individuals in academic, government, the private sector, and nonprofits/NGOs. Most sessions were themed around a particular topic (ethics and fairness; novel data collection methods; public services; etc.) and presenters would discuss research they had done in the area or examples of implementation. Some of the most interesting talks we attended were on equity in 311 call reporting, creating a database of police killings, and patterns in civil asset forfeiture. There was also a poster session and reception at the end of the day.
Shouvik Mani presenting at Data for Good Exchange, 2017
Shouvik Mani presenting about the Intelligent Pothole Detection project at the Data for Good Exchange conference, 2017
 One of the highlights was getting to see Shouvik Mani, Umang Bhatt, and Edgar Xi of Carnegie Mellon talk about their Intelligent Pothole Detection project. Shouvik is currently serving as in a Assistant Director for Data Projects role with SUDS and will be the Director of SUDS beginning in January 2018.

Infographic Workshop: Thursday, October 5

Infographic Design Workshop with Jessica Bellamy

On Thursday, October 5, Jessica Bellamy will lead interested students in a workshop on Infographic Design. Jessica is an Infographic Designer and Adobe Creative Resident for 2017. With her guidance, we will explore and apply principles of conscious and responsible design to a real-world infographic project.


Jessica will cover the following topics:

  • Icon drafting
  • Infographic composition
  • Power dynamics in design
  • Data framing
  • Asset v. deficit mapping
  • Access to information
  • Grassroots design strategies
Chris Worley, Jessica Bellamy, and Ali Siegel after the Infographic Workshop
Chris Worley, Jessica Bellamy, and Ali Siegel at the Infographic Workshop

Infographics are easily digestible visualizations of complex data. As our access to larger volumes of data increases, our ability to communicate findings to policymakers, people with resources, and low-opportunity communities becomes more important.

If you’re interested, make sure you’re registered on EventBrite! The event will be on Thursday, October 5 from 12:00-1:15pm in Hamburg Hall, Room 2003.

Census Data Workshop: Monday, October 2

Navigating U.S. Census Data Workshop with Eileen Patten 

Eileen Patten presenting at the Census event
Eileen Patten presenting at the Census event

Monday, October 2, join us for a workshop on accessing and using U.S. Census Bureau population and business data to assess your community, explore a topic of interest to you, or just learn more about the United States. U.S. Census data is a treasure trove of information about our country that spans many decades and many topic areas. Did you know you can use the American Community Survey to figure out how many homes in the U.S. have flush toilets? Or the American Time use Survey to find out how many hours Americans spend mowing their lawns?


This workshop will be led by the SUDS Speaker Series Chair, Eileen Patten. She is a second year Master of Science in Public Policy and Management student, specializing in Data Analytics. Before coming to Heinz, Eileen used census data to perform analysis on topics like gender and racial wage gaps, Latino and Asian populations in the U.S., and teen birth rates while working for the “fact tank” Pew Research Center.

Eileen will introduce several tools and surveys, including:

  • Integrated Public Use Microdata Series (IPUMS-USA): IPUMS-USA collects, preserves, and harmonizes U.S. census microdata and provides easy access to this data with enhanced documentation. Data includes decennial censuses from 1790 to 2010 and American Community Surveys (ACS) from 2000 to the present. Eileen will be working through the IPUMS online tabulator and dataset downloading. You can sign up for an IPUMS account if you want to follow along!
  • American FactFinder: This is the Census Bureau’s main tool for distributing information collected by their programs. Data from the Decennial Census, the Economic Census, the American Community Survey, the American Housing Survey, and many more.
  • QuickFacts: This “is an easy to use application that provides tables, maps, and charts of frequently requested statistics from many Census Bureau censuses, surveys, and programs”. (QuickFacts)

If you’re interested, make sure you’re registered on EventBrite! The event will be on Monday, October 2 from 4:30-6:00pm in Hamburg Hall, Room 2008.

Welcome to a new semester with SUDS!

Wei, Ben K, Michael, Ben S, Chris, Vrishali, Akanksha, Eileen, Shouvik, Ali

Subscribe to keep up to date with SUDS

About Us

Let us reintroduce ourselves – Students for Urban Data Systems (SUDS) is a group of intellectually curious students at CMU dedicated to solving real life problems. We believe data analysis, data visualization, and machine learning skills are key to understanding and responding to issues in today’s data-heavy world. Unfortunately, many community organizations are not always equipped to do this type of data manipulation and analysis. That’s where we come in.

SUDS partners with organizations in Pittsburgh and Allegheny Country that are dedicated to social good, and we lend our skills to their mission. In sum, we connect our members with opportunities to do good with data.

Who We Are

In 2015, a small group of students recognized an opportunity to combine the skills they were learning in class with their ambition for contributing to the welfare of community organizations. That idea was the seed for SUDS. In two short years, we have grown from the original group of five students to a network of 50+ regular members, with hundreds of students participating in our activities in the past two years.

Obviously, our founders tapped into something that excited students across the CMU community. Today, students from all academic disciplines and skill levels participate in SUDS projects, workshops, hack nights, and speaker series.

What Makes Us Unique

We prize enthusiasm and effort before skill set. Our projects help members develop their skills, including data analysis (Python, R), data visualization (R Shiny, GIS, JS), machine learning, and project management. One of the most important parts of the SUDS experience is our mentorship. We learn from each other and help each other grow. Finally, we are open to all. There is no pay to play with SUDS. It’s as simple as this: our members are the folks that show up. You can keep up to date with projects, workshops, and events in the SUDS community by subscribing to our mailing list and community discussion board:

The Legacies of Redlining in Pittsburgh

by Devin Rutan

Pittsburgh is still defined by a geography of uneven development where modern disparities were built from historic patterns of discrimination. While searching through PghSNAP, I was struck by the similarities between the survey of prevailing building conditions and the Home Owners Loan Corporation (HOLC) map of 1937. So, I created a GIS-based framework to assess the legacies of neighborhood appraisal and lending discrimination in Pittsburgh by intersecting the HOLC map with census data.

1 & 2
Current building conditions & 1937 Home Owners Lending Corporation (HOLC) divisions

Before getting swept up in the analysis, I want to be clear about what the HOLC map is and what it represents, so in the interest of brevity, I have highlighted some of the key aspects of the history. For a more thorough (perhaps too thorough) version you can read the full paper: here.

In the 1930’s, the federal government fundamentally transformed the mortgage market, creating the 30 year mortgage packages that make home-ownership accessible. In an effort to address perceived weaknesses in the housing market, federal officials advocated more ‘scientific’ appraisal methods. Appraisal ideology was forged within a climate of prejudice generally pervasive throughout white society, explicit institutional discrimination at most levels of government throughout the United States, and a heavily skewed distribution of economic power; policy makers saw little value in poor, African-American, immigrant, or Jewish communities and even viewed them as a direct threat to the value of middle class, white communities.

The maps are terrific localized representations of appraisal practices in each of the 239 cities they depicted. The HOLC maps were not directly published and used by bankers and appraisers to make lending decisions but were, nonetheless, certainly influential in the development of biased appraisals: the federal government published the tools, rationales, and examples necessary for banks to create maps of their own.

The first portion of my investigation tried to understand more about the impact of these practices at the time they were being honed. I intersected the 1940 Census, obtained from NHGIS, with the HOLC map. One of the strongest relationships within the appraisal of Pittsburgh neighborhoods was racial segregation. In the graph below, I arranged the communities by their HOLC ranking and then plotted the percentage of white residents in the tract (at this time, Pittsburgh had virtually only two racial groups). Looking at the four plots together, it is clear that a huge portion of Pittsburgh, regardless of value, was exclusively white. The dashed blue line represents the overall percentage of white people in Pittsburgh at the time; if communities were not segregated by race, they would hover around this line. Now consider the valuation of the tracts: not only were African Americans concentrated into a handful of places but they were relegated the lowest quality neighborhoods that were considered to be the least valuable (partially because of their presence). Also, a methodological aside, because census tracts encompass an aggregated area, segregation at the block level could only be starker.


Next, I explored how these historic practices have continued to shape Pittsburgh. I used standardized census data to identify entrenched neighborhood characteristics from 1970 to 2000. Tracts that persistently had the largest proportions of African Americans were almost entirely aligned with red and yellow areas as you can see in the map below. Three main clusters of African American residents appeared: the Hill District, Manchester, and Homewood. These are communities that were historically considered the least valuable and were undermined economically and are, at least in part, still dealing with the effects. Further, tracts that persistently had the highest concentrations of poverty were also heavily focused in red and yellow areas. Red and yellow tracts were also much more susceptible to population loss than green or blue areas as you can see in the graph below. In many ways these spaces have held their position through time and the access, or lack of access, to mortgage financing had long reaching legacies. Groups that historically were victimized by appraisal ideology continue to occupy these spaces. These neighborhoods are likely less stable as well, considering the large presence of poverty and heaviest population losses.

Black communities have suffered from disinvestment
Pittsburgh’s uneven decline in population, 1970-2000

On the other hand, those communities that were uplifted by their historic value largely retained their status into modern times. Tracts with persistently the highest average incomes, home-ownership rates, even for African Americans, and the highest average values were all largely aligned with the historic green or blue categorizations. These communities benefited from unfettered access to the mortgage market and became the most stable, affluent neighborhoods in Pittsburgh because of their relative health. As you can see in the map for highest average values, Squirrel Hill, in particular, maintained its position. The disproportionate access to mortgage funds even continues today: according to PCRG, 7 neighborhoods received 50% of all mortgage dollars in 2015—6 of the 7 were historically rated either green or blue.

Wealthy communities benefited from redlining

What is clear from the assessment of Pittsburgh’s geographic legacies of redlining is that the city is still largely defined by an ugly history of uneven development. As much as we may like to think that we have moved beyond pre-World War 2 or pre-Civil Rights Pittsburgh, we live in a city that is still, at least somewhat, constructed the same way. Policies that have attempted to create equality and opportunity for parts of the city that were left behind have failed to do so. Those parts of the city that were built on their exclusion have maintained their privileged and elevated status. Today, as we are having debates about neighborhood quality, accessibility, and inclusion, we must remember the specific history of uneven development. Are we comfortable with this geography? If not, what are we willing to do, lest it define us for another 60 years?


Devin Rutan graduated from the University of Pittsburgh with a Bachelors of Philosophy in Urban Studies and studied Applied Statistics and GIS. Devin cares about housing and neighborhood development and is currently working with the Northside Coalition for Fair Housing and the Pittsburgh Tenants Union. Originally from the DC area, Devin is an avid basketball fan: Let’s go Wizards! You can follow his work here or connect with Devin here: