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

Author

Leigh, Jason ; Johnson, Andrew E. ; DeFanti, Thomas A. ; Bailey, Stuart ; Grossman, Robert

Author_Institution

Electron. Visualization Lab., Illinois Univ., Chicago, IL, USA

fYear

1999

fDate

1999

Firstpage

62

Lastpage

69

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

Keywords

data mining; data reduction; data visualisation; feature extraction; groupware; meta data; virtual reality; ImmersaDesks; collaborative exploratory analysis; collaborative immersive virtual environments; collaborative visualization; decimation; desktop workstations; feature detection; high-end visualization interface; massive data sets; massive data-set culling; meta-data creation; partitioning; reduced data-sets; remote CAVEs; summarization; tele-immersive environments; viewing; Collaboration; Collaborative work; Data analysis; Data mining; Data visualization; Humans; Physics computing; Rendering (computer graphics); US Department of Energy; Virtual environment;

fLanguage

English

Publisher

ieee

Conference_Titel

High Performance Distributed Computing, 1999. Proceedings. The Eighth International Symposium on

Conference_Location

Redondo Beach, CA

ISSN

1082-8907

Print_ISBN

0-7803-5681-0

Type

conf

DOI

10.1109/HPDC.1999.805283

Filename

805283