Abstract
This paper introduces web-based interactive Linked Micromap (LM) plots, a set of dynamic visualization methods that allows readers to interactively select variables and modify the different views to help reveal relationships among the study units. This methodology provided the foundation for web-based micromaps used by the National Cancer Institute (NCI). This illustrates the power of visualization to make statistical summaries involving health and risk factors for millions of people accessible to health planners than may have never had a statistics class. LM plots methodology is in use by the Department of Agriculture and readily extend to other application in other agencies in the United States. The interactive methods can be as useful in such extensions as they were for the National Cancer Institute
Highlights
Linked Micromap (LM) plots constitute a new template for the display of spatially indexed statistical summaries [1, 2]
LM plots methodology is in use by the Department of Agriculture and readily extend to other application in other agencies such as the Department of Homeland Security
The LM plots for displaying the cancer summary statistics have four parallel sequences of display panels, which are US/shows that the study units (States) micromap, State/County name, and two cancer statistical summaries
Summary
Linked Micromap (LM) plots constitute a new template for the display of spatially indexed statistical summaries [1, 2]. This paper introduces web-based interactive LM plots, a set of dynamic LM visualization methods that allows readers to interactively select variables and modify the different views to help reveal relationships among the study units. This methodology provided the foundation for web-based micromaps used by the National Cancer Institute (NCI) [9, 10]. The test-bed list of selectable cancer sites is restricted to breast, colon, prostate, and lung, but readily extended These web-based interactive LM plots have preserved all the key features of the LM plots originally published. Since the Internet is a widely accessible source of public information, the web based implementation of LM plots will make information available to more readers while the new interactivity can lead to more involvement and better understanding
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