In this work, we simplify and enhance the visualization currently supported by the UC Atlas Website for mapping global inequality by (i) creating a simple user interface, (ii) supporting time series animation of global maps, and (iii) simplifying and integrating theline graphs, bar graphs, and ranked bar graphs. The visualization system is accessible at http://atlas-dev.ucsc.edu/ian. Our vision is to enhance the visualization system by adding additional types of charts including scatter plots, star plots, parallel coordinates, and small multiples visualization while keeping the user interface simple and integrated.

In this work, our objective is to visualize the relationship between the variables that impact health in a global context. Recently, Cornia et al. [1] have proposed five main determinants of global health – material deprivation, progress in health technology, acute psychosocial stress, unhealthy lifestyle, and income inequality etc. Results of regression analysis worldwide indicate that almost 90% of the variation in health can be attributed to twelve variables representing these five determinants. We compute correlations between the health variables and its determinants and apply a visualization tool [2] to display these correlations globally and at country level in order to gain a better understanding. We observe that the country-level results obtained through easy-to-understand graphs and simple correlation analysis pose an anomaly to the worldwide regression results and require further analysis to close the gap between correlation and regression analysis and the gap between the country-level and global-level analysis.