Visualizing Data
Using Linked Micromap Plots to Characterize Omernik Ecoregions
Data Mining and Knowledge Discovery
dg.o '03 Proceedings of the 2003 annual national conference on Digital government research
Analyzing statistical relationships between global indicators through visualization
ICTD'09 Proceedings of the 3rd international conference on Information and communication technologies and development
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This paper introduces interactive extensions to two recently developed templates for displaying geospatially-indexed estimates. The first template, linked micromap plots, links small generalized maps with statistical panels that describe regions. Research centered at the National Cancer Institute addressed the task of communicating state and county cancer statistics and tailored this template to show estimates, confidence intervals, and Healthy People 2010 target values. The research also integrated interactive options, such as variable selection, sorting, fixed header scrolling, mouse tips, enlarged dynamic map views and drill down, in a Java applet. This template has fared well in early usability tests. The second template, called conditioned choropleth maps, seeks to improve hypothesis generation about the spatial patterns shown in a classed choropleth map. Since variation of a study variable is often related to known risk factors, the template provides a way to control for the known variation. This paper describes dynamic sliders that change class boundaries for a study variable and that partition regions into a 3 x 3 layout of maps based on values of two risk factors. Highlighted regions in each map are more homogeneous with respect to both risk factors. Comparisons across maps and spatial patterns within maps provide the basis for generating hypotheses. The JAVA application shareware also includes dynamic statistical annotation and QQplots for comparing distributions