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Mapping our Communities

The challenge

For an unnamed foundation, we developed an interactive map that crunches and summarizes the numbers from over 70 social, economic, health, & educational data measures

The US Census and an ecosystem of governmental and NGOs have a wealth of data to describe a given moment in the United States (for example, from the Dept. of Commerce, the CDC, and many public-interest NGOs). But they are reported in different granularities, and these datasets don’t talk to each other.

Design strategy

Our map used a consistent methodology across every square mile of the United States to identify the areas of privilege vs. impoverishment — terms grounded in the real-life outcomes experienced by its residents.

This process was both exploratory and iterative, beginning with a survey of potential national datasets that are publicly available, free, and that relate to one of the overall themes of health, economic well-being, socio-economic factors, demographics, education, environment, and crime. In total we identified 390 datasets plus another 1,250 measured indicators inventoried in the most recent (2012-2016) American Community Survey.

To organize the data, we developed a conceptual model of four “Composite Scores”: (1) Educational strength in the community, (2) Economic opportunity in the community, (3) Neighborhood strength in the community, and (4) Health in the community. These were further divided into 12 sub-indices. Each sub-index aggregated numerous data indicators in smaller groupings under these categories.

With four composite scores, it is then possible to aggregate them to a single summary Index.  Of course, no single number can possibly capture the diverse lived experiences in one place. But this number helped to quickly identify which communities of the United States are experiencing, overall, very positive results in the last 15 years, versus those communities which are experiencing, overall, consistently negative outcomes on those same indicators.


  • Data research and summarization
  • Robust normalization, z-scoring, and GIS analysis
  • Number crunching across 250,000 block groups
  • User research to create an intuitive UI
  • Web development

a colorful map showing areas of deep blue to deep red, across the greater Chicago area