Tag Archives: data

The linked map interface shows secondary educational attainment for the world by country and US by county.

One Map, Two Map: Visualizing Social Disparities through Linked-Scale Interactive Maps

Description

People’s quality of life or socioeconomic status can greatly differ based on where they live, whether they live in different cities, different counties, or in different countries. These inequalities and disparities can be and have been measured using indicators related to the different facets of life: wealth, education, health, and even happiness. Communicating where and how those inequalities affect different people and geographical areas to the public in an effective and engaging way is imperative to progress towards a more equitable society. Information visualization, and specifically maps, are a successful mechanism for conveying these differences in quality of life and engaging people in caring about larger issues and other people.

This project investigates how people perceive socioeconomic disparities using an interactive choropleth map visualization where users can change the map to display different socio-demographic indicators, including income inequality, life expectancy, educational attainment, rate of incarceration, and prevalence of HIV/AIDS and obesity. We implemented two versions of the interface: one displaying the United States only by county, and another arranging the United States map and a country-level choropleth map of the world by country, side-by-side. We conducted between-subjects A/B user testing where we surveyed and interviewed users before and after interacting with one version of the map.

Figure 1: Choropleth map of the Secondary Educational Attainment indicator in the United States only, by county
Figure 2: Choropleth map of the Secondary Educational Attainment indicator in the United States, by county (on the right) and in the world, by country (on the left)

We hypothesize that interacting with either map will lead to stronger feelings about the intensity of inequality in the U.S., and more confidence in their opinions on disparities. Additionally, we hypothesize that interacting with a contextualized map of the U.S. within the world will influence the user’s perceptions of the U.S. differently than when interacting with the U.S. map only.

Project Team

  • Dr. Clio Andris, Georgia Tech
  • Grant Jones, Georgia Tech
  • Yasmine Belghith, Georgia Tech
  • Kurt Heischmidt, Georgia Tech
  • Dr. Joshua S. Weitz, Georgia Tech
  • Dr. Jessica Roberts, Georgia Tech

Coal Pollution Impacts Explorer

Description

When Sulfur Oxides (SOx) are emitted from power plant facilities, they do not fall directly to the ground. They are carried by air currents, sometimes great distances. Modeling of atmospheric transport and dispersion of these particles can estimate fine particulate matter (PM2.5) source impacts attributable to SOx emissions from each of the more than 1,200 coal-fired electricity generating units in operation in the United States between 1999-2018.

The Coal Pollution Impacts Explorer (C-PIE) is a web-based interface designed to visualize and scaffold atmospheric data and modeling for a public audience. Users can investigate the sources of pollution in their home county’s air, examine where pollution from a nearby facility disperses, and explore trends over time as facilities install pollution-mitigating scrubbers in response to legislative actions.

Research on the C-PIE platform investigates how data interactions can be scaffolded to support inquiry and engagement for public audiences.

The interactive C-PIE platform can be found at: https://cpieatgt.github.io/cpie/

Below you will find representations of some of our iterative development work on the platform. To read more about the impacts of coal pollution, read our recent article in the Journal Science:

Henneman, L., Choirat, C., Dedoussi, I., Dominici, F., Roberts, J., & Zigler, C. (2023). Mortality risk from United States coal electricity generation. Science, 382(6673), 941-946. https://doi.org/10.1126/science.adf4915

Images & Videos

Research Team

  • Jessica Roberts
  • Lucas Henneman (George Mason University)
  • Sue Reon Kim, MS-HCI 2021
  • Srijan Jhanwar, MS-HCI 2022