Java-based Dynamic Linked Micromap Plots
Jim X. Chen, (George Mason University), firstname.lastname@example.org,
Xusheng Wang, (George Mason University), email@example.com,
Daniel B. Carr, (George Mason University), firstname.lastname@example.org,
B. Sue Bell (National Cancer Institute), email@example.com, and
Linda W. Pickle, (National Cancer Institute), firstname.lastname@example.org
Linked Micromap plots (LM plots) constitute a new template for the display of spatially indexed statistical summaries. It can be used to visualize various complex data in many areas. This paper extends the existing work by introducing Java-based Dynamic 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.
We use sample cancer statistics from the National Cancer Institute (NCI) as an application and implementation example to present the methods. The data set is not official data, but we believe that it provides an excellent test-bed for statistical visualization study. The system of interactive LM plots that we developed will allow NCI to present the cancer statistical summaries of the United States at the state and county level on the Internet. These Java-based dynamic LM plots have preserved all the key features of the original LM plots, and further allow better visualization through drill-down views, sorting, multiple levels of detail, magnified micromap, miniature overall statistical summary, confidence interval switching, and other interactive visualization methods to visualize the data and the relationships from different perspectives. We believe that the methods and implementations bring new ideas into statistical data visualization that allows more diversity, clarity, and convenience of presentation.