The project will leverage GeoVISTA Studio as an environment for building and testing software applications focusing on exploratory spatial data analysis applied to cancer and related risk factor data. During the course of the project, we will create and disseminate software developed. Those interested in more information about GeoVISTA Studio can learn more and obtain the software from: http://www.geovistastudio.psu.edu/.

Applets:

These applets are demonstration versions using U.S. Census data. Users can try their own data with the tools by accessing Studio. Feedback is welcome! Please contact Frank Hardisty (hardisty@sc.edu) with any comments or questions.

All applets require Java Plug-in 1.3 or later and Javacript enabled. To view an applet, click on its respective image. Please respect this software's licenses (see below).

Univariate Map This map applet features interactive spatial tools and color selection tools. Users can create a multipart line through color space to better visualize spatial patterns. Author(s): Frank Hardisty   Bivariate Map Users can create bivariate color scemes that allow users to visualize spatial patterns between two variables simultaniously. Author(s): Frank Hardisty   Parallel Coordinate Plot Users can see mulitvariate statistical patterns using this interactive tool. Author(s): Flo Lederman (Parvis), Frank Hardisty   Map and Scatterplot Matrix This image shows a map and scatterplot matrix. The position and the coloring of the observations is determined by the variables on the diagonal in the scatterplots, while in the map, position is geographic, and color is determined by the variables. Using this tool, we can see attribute and geographic relationships between multiple variables at a time. Author(s): Xiping Dai, Frank Hardisty   Map and Linkgraph This applet containts a map linked to a node-and-edge graph representation of U.S. states, where states are nodes and links between them are determined by the counties similarity in one or more variables, as found by the minimum spanning tree in attribute space. We can use this tool to explore the geographic relationships between similar observations. Author(s): Alex Shapiro (Touchgraph), Frank Hardisty, Diansheng Guo   Subspace Browser Here the nodes are variables, and the graph shows the minimum spanning tree based on their correlation coefficients. This is an easy way to rapidly browse relationships between many variables. Author(s): Alex Shapiro (Touchgraph), Frank Hardisty, Diansheng Guo

Source code for the above software will be available soon. All software licensed under the GNU Lesser General Public License , with the following exceptions: The Parallel Coordinate Plot is based on Parvis, making this code licensed under the GNU General Public License. The touchgraph based Linkgraph is Apache licensed.