SemanticPrism: A multi-aspect view of large high-dimensional data
Victor Yingjie Chen, Ahmad M Razip, Sungahn Ko, Cheryl Zhenyu Qian, David S. Ebert · 2012
VAST 2012 Mini Challenge 1 Award: Outstanding integrated analysis and visualization. We present a visual analytics system SemanticPrism, which aims to analyze large-scale high-dimensional datasets containing logs of a million computers. SemanticPrism visualizes the data from three different perspectives: geo-temporal, time series curve, and pixel visualization. With each perspective, we use semantic zooming to present more detailed information.