CGVis is a generic data visualization tool with an innovative zoomable user interface and animations which helps users to explore multidimensional data and find particular features in it. CGVis was greatly inspired by HCE (Hierarchical Clustering Explorer) of the University of Maryland. It was conceptually designed at the Graz University of Applied Sciences FH JOANNEUM by Jochen Martin, Karl Lampret and Ilya Boyandin and was then developed by Ilya Boyandin and Erik Körner. CGVis runs on any Java SE-enabled platform.
Features:
- Zoomable heat map view providing an overview of the whole input dataset
- Hierarchical clustering of elements and attributes
- Dendrogram in the heat map view
- Zoomable scatter plot view (2, 3, or 4 selected attributes are visualized by the dots' positions, sizes, and colors)
- Smooth animation in the scatter plot view when changing the axe/size/color attributes
- Element selection synchronization between the views
- Support for CSV input files
- Support for the XML-based CGV file format that provides facilities to load the input data from a database (see CGVis DataSources for details)
- Input data normalization (enabled by default)
Requirements:
- Java Standard Edition 5.0+ (can be freely downloaded here)
Watch this demo for a quick overview (you can also download the demo as a zip archive here).
If you have any questions or suggestions about CGVis, feel free to contact me via email: ilyabo@gmail.com.
