Transparent Data Cube for Spatiotemporal Data Mining and Visualization

Data mining and visualization in very large spatiotemporal databases requires three kinds of computing parallelism: file system, data processor, and visualization or rendering farm. Transparent data cube combines on the same hardware a database cluster for active storage of spatiotemporal data with an MPI compute cluster for data processing and rendering on a tiled-display video wall. This approach results in a scalable and inexpensive architecture for interactive analysis and high-resolution mapping of environmental and remote sensing data which we use for comparative study of the climate and vegetation change.