A methodology for supporting collaborative exploratory analysis of massive data sets in tele-immersive environments

Abstract

This paper proposes a methodology for employing collaborative, immersive virtual environments as a high-end visualization interface for massive data-sets. The methodology employs feature detection, partitioning, summarization and decimation to significantly cull massive data-sets. These reduced data-sets are then distributed to the remote CAVEs, ImmersaDesks and desktop workstations for viewing. The paper also discusses novel techniques for collaborative visualization and meta-data creation.