2018 Project Season

Begin in January. Demo in June. 


Disaster Resilience

Call to action: 

Let's take a hard look at our vulnerability as a city, and make actionable recommendations that can help to save lives and save critical infrastructure. 


While the event of a catastrophic earthquake in the Pacific Northwest may be unpredictable, science tells us it's inevitable.  We should be using the best information available to prepare for disaster and plan for resilience.  Yet, emergency prevention is often overlooked and underfunded in a variety of ways--- including data analysis.  

One of Hack Oregon's most widely visited projects is Aftershock, a tool that generates custom reports for seismic preparedness across Oregon.  This year,  we're going to focus on in-depth analysis for the City of Portland. 

Key Questions

  • How can data more effectively enable cities to assess risk, consequence and direct resources for preparedness as part of a proactive disaster planning process?
  • Where is critical infrastructure most fragile in the City of Portland, and does this disproportionally affect already vulnerable communities? 
  • How do social factors strengthen a community's ability to resist and bounce back from a disaster,  and can these factors be measured? 
  • What resources can we publish that are reproducible to support data-driven disaster planning in other cities and regions?

Transportation Systems

Call to action

What do we know today that can guide the transportation infrastructure for Smart Cities of tomorrow?


Newly released findings from TriMet shows a slow decline in public transit ridership over the last 10 years, a pattern which appears to be consistent across the nation.  While the cause of decline in ridership doesn't point to a single variable, it's been suggested that housing affordability and economic displacement may play a role in this phenomenon. 

The transportation project this year will dive deeper into a spectrum of data sources and multivariable analysis that can illuminate a fuller picture of demand and equity in our evolving transit ecosystem. 

Key Questions

  • How equitable is our public transit system? Is it true that public transit works less well in places where people need it the most? If it is true; how true is it? 
  • Is economic displacement a driver of transit ridership loss? 
  • Is it true that cost of living increases in the urban core have pushed residents outside optimal transit service areas? 
  • What is the relationship between increased density and declining demand? 
  • Considering the accelerated development of multi-modal transportation options, including bike sharing, TNC platforms and "rideshares", autonomous vehicles and last mile solutions, what data do we have to help understand the role of public transit in the future? 

Housing Affordabilty

Call to Action

Synthesize complex information to understand the state of housing market and promote a vision for long-term affordability.


Over the past 10 years, the United States housing market has been dominated by two major trends: a surging demand in the rental market and a crash in the rate of homeownership.  The 2017 State of the Nation's Housing Report by the Joint Center of Housing Studies at Harvard University shows these trends are particularly evident in Portland.  

With house prices rising faster in Portland than the rest of the country, the deepening gap between income and home prices may not be a bubble but a long-term shift that will restructure the cost of housing in our city.  In a recent City Club interview, Dr. Christopher Herbert, managing director of JCHS, said Portland is "ground zero for gentrification." 

Building on our project from last year's CIVIC Housing Theme and Homelessness Theme, JCHS's National State of Housing Report, and The City of Portland's State of Housing report, we can tell a story that speaks to our city and brings a data-driven perspective to upcoming policy decisions in Portland. 

Key Questions

  • To what extent are national trends in housing affordability evident in Portland's market?
  • What are key demographic drivers in local housing trends and what do we know about disproportionate access to opportunity?
  • Does available data establish a link between rising cost of housing and increasing homelessness in Portland? 
  • If no-cause lease evictions leave no data trail, what other data sources can we use to reliably approximate displacement?
  • What new data can we provide to engage and inform City Council on balanced and effective policy action?

Local Elections

Call to action

connect the dots between money, influence, and the future of redistricting in our state. 


Oregon is preparing for our 10-year redistricting process, which means drawing the geographic boundaries to create electoral districts for congressional and legislative representatives. In a recent op-ed, Secretary of State Dennis Richardson stated, "Oregon’s legislature is responsible for redrawing district lines objectively. However, partisanship and incumbency can unduly influence how districts are reshaped. Many states around the country have realized this problem known as gerrymandering."

Drawing district boundaries fairly, taking into account factors such as ethnicity, political affiliation, and socioeconomic status is an enormously complex information challenge.  Let's assemble an elite data team to conduct independent research and data analysis to try to understand how changes and tradeoffs in redistricting might affect the next 10 years of Oregon elections.  We'll publish this in an open, visual format to support the Redistricting Task Force and drive public engagement toward a balanced outcome. 

Key Questions

  • How much of a difference does money really make in statewide and local elections?
  • What can money tell us about influence in a local election cycle?  Where does money fall short compared to other influence factors?  
  • Is it possible to measure, in real time, how much influence you have as a voter in a local election?
  • To what degree are local election outcomes predictable? What influencing factors contribute to making election outcomes predictable or surprising? 
  • Do current district boundaries bias outcomes?  How can data analysis and visualization engage the public in the complicated task of redistricting in 2020? 

Neighborhood Development

Call to action

Visualize and compare patterns over time to understand the multifaceted history of change in Portland neighborhoods. 


All of us have felt the impact of rapid change and growth in Portland, but it can be hard to quantify in real terms. 

When we talk about a "neighborhood", we're talking about a lot of things: schools, roads, crime, housing, businesses, parks.... everything.  But when we think about how neighborhoods are managed at the municipal level, the conversation and the accountability structures become more segmented. Data that exists on neighborhoods are often fractured across departments, with inconsistent standards, and in technical terms--- very often "don't relate".  

However, there are two things almost all data sources have in common: time and space.  

The theme this year on Neighborhood Development is special because, in addition to tackling some of the toughest architecture challenges of the season, their work supports integration opportunities for every single other theme.  Together, this project represents the backbone of an evolving time-based and geospatial reference tool that powers the entire CIVIC platform. 

Key Questions

  • How does our perception of change in Portland's neighborhoods stack up to quantifiable patterns?
  • What can the analytical history of permit data tell us about our priorities as a city?  
  • How have our school systems adapted throughout changes in density, affordability, and demographic shift?  How could data inform current boundary challenges for PPS?
  • What are long-term trends in crime and public safety in our neighborhoods?
  • How does the development of transit infrastructure (or lack of access) affect neighborhoods?
  • How does a small business ecosystem affect a community?
  • Are there early predictors of a sharp rise in the cost of living or what we think of as other classifiers of "gentrification"? 
  • What effects can we measure by studying patterns in leadership and budgetary decisions over time?