Collaborative Visualization: Topological Approaches to Parameter Tweaking for Informative Volume Rendering

Data crisis ubiquitously arises in solving complex scientific problems. It has motivated us to develop a Collaborative Visualization Environment (CVE), which provides the users with the "serendipity" with the aid of effective data-centric tweaking of visualization-related parameters. To this end, we have proposed the concept of Volume Data Mining (VDM), which takes full advantage of knowledge in the field of differential topology to allow the users to explore the global structures and local features of target 4D volumes. In this paper, the effectiveness of our current CVE framework with several VDM tools is illustrated with applications to practical scientific simulation datasets.