Examining the causes and consequences of environmental inequality over time: A data-driven computational approach
The body of interdisciplinary scholarship examining the causes and consequences of environmental inequality assesses both the socioeconomic determinants of toxic pollution exposure and how this exposure relates to adverse community outcomes. Although environmental justice (EJ) scholars agree that (1) inequities in pollution exposure exist by both race and class and (2) these exposures result in adverse community outcomes from both health and quality-of-life standpoints, few studies look into how patterns change over time. Our group will work closely with the SESYNC data science experts to build a cyberinfrastructure system that will both allow researchers to answer socio-temporal research questions and produce exploratory visualization—a vantage point where new discovery can occur. By creating this type of integrated cyberinfrastructure, we will gain new insights into the relationship between socially structured correlates and environmental injustice from both scholarly and actionable science points-of-view.