2012 IEEE Conference on Visual Analytics Science and Technology (VAST) 2012
DOI: 10.1109/vast.2012.6400527
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SemanticPrism: A multi-aspect view of large high-dimensional data

Abstract: 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.

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Cited by 5 publications
(2 citation statements)
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“…Most of the challenge entries used maps and statistical graphs. For example, Chen et al [18] and Choudury et al [19] used one 2-D map to visualize the overall computer statuses in a given time and a slider to adjust the time. Dudas et al [20] used time series curves to show the aggregate trend of certain qualities.…”
Section: Visualization Methods Of W3 Attributesmentioning
confidence: 99%
See 1 more Smart Citation
“…Most of the challenge entries used maps and statistical graphs. For example, Chen et al [18] and Choudury et al [19] used one 2-D map to visualize the overall computer statuses in a given time and a slider to adjust the time. Dudas et al [20] used time series curves to show the aggregate trend of certain qualities.…”
Section: Visualization Methods Of W3 Attributesmentioning
confidence: 99%
“…Our implementation of representational fluency was developed on a visual analytics system SemanticPrism [18]. It won the award of "outstanding integrated analysis and visualization" in the VAST 2012 MC1.…”
Section: Context -Data and Systemmentioning
confidence: 99%