The ability to extract meaning from the huge amounts of data obtained from simulations, experiments, sensors, or the
world wide web gives one tremendous advantage over others in the respective area of business or study. Visualization
becomes a hot topic because it enables that ability. As data size is growing from terascale to petascale and exascale, new
visualization techniques must be developed and integrated into data analysis tools and problem solving environments so
the collected data can be fully exploited. In this talk, I will point out a few important directions for advancing the
visualization technology, which include parallel visualization, knowledge-assisted visualization, intelligent visualization,
and in situ visualization. I will use some of the projects we have done at UC Davis in my discussion.