Issue No. 01 - January/February (2007 vol. 27)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2007.6
Jian Huang , University of Tennessee, Knoxville
Huadong Liu , University of Tennessee, Knoxville
Micah Beck , University of Tennessee, Knoxville
Andrew Gaston , University of Tennessee, Knoxville
Jinzhu Gao , Oak Ridge National Laboratory
Terry Moore , University of Tennessee, Knoxville
There has been a recent trend for large groups of users to collaborate on large data sets across geographical distances. In this context, if users could share and modify a visualization over the standard Internet without requiring local replication of the data, the visualization community would have an even greater impact on the conduct of today's research. Various remote and collaborative visualization approaches have been proposed. This article presents a different viewpoint. The authors believe that for dynamic sharing of large-scale visualization, distributed heterogeneous resources that are free, unscheduled, and unreserved could serve as a fundamental and sufficient platform to support large groups of users--with greater potential usability, scalability, and cost efficiency.
distributed visualization, collaborative visualization, parallel visualization, fault-tolerance, and scalable visualization
J. Gao, A. Gaston, T. Moore, M. Beck, H. Liu and J. Huang, "Dynamic Sharing of Large-Scale Visualization," in IEEE Computer Graphics and Applications, vol. 27, no. , pp. 20-25, 2007.