R. Machiraju, J. E. Fowler, D. Thompson, W. Schroeder, and B. Soni, "EVITA: A Prototype System for Efficient Visualization and Interrogation of Terascale Datasets," Tech. Rep. MSSU-COE-ERC-01-02, Engineering Research Center, Mississippi State University, November, 2000.
Large-scale computational simulations of physical phenomena produce data of unprecedented size (terabyte and petabyte range). Unfortunately, development of appropriate data management and visualization techniques has not kept pace with the growth in size and complexity of such datasets. To address these issues, we are developing a prototype, integrated system (EVITA) to facilitate exploration of terascale datasets. The cornerstone of the EVITA system is a representational scheme that allows ranked access to macroscopic features in the dataset. The data and grid are transformed using wavelet techniques while a feature-detection algorithm is used to identify and rank contextually significant features directly in the wavelet domain. The most significant parts of the dataset are thus available for detailed examination in a progressive fashion. The work described here parallels much of the work in the traditional data-mining community at least in essence. After having described the basic system prototype, some ongoing work is described. We focus on our efforts in multiscale feature detection and progressive access to two-dimensional vector fields derived from an oceanographic dataset.