Brushing Moments in Interactive Visual Analysis

dc.contributor.authorKehrer, Johannesen_US
dc.contributor.authorFilzmoser, Peteren_US
dc.contributor.authorHauser, Helwigen_US
dc.contributor.editorG. Melancon, T. Munzner, and D. Weiskopfen_US
dc.date.accessioned2014-02-21T20:05:49Z
dc.date.available2014-02-21T20:05:49Z
dc.date.issued2010en_US
dc.description.abstractWe present a systematic study of opportunities for the interactive visual analysis of multi-dimensional scientific data that is based on the integration of statistical aggregations along selected independent data dimensions in a framework of coordinated multiple views (with linking and brushing). Traditional and robust estimates of the four statistical moments (mean, variance, skewness, and kurtosis) as well as measures of outlyingness are integrated in an iterative visual analysis process. Brushing particular statistics, the analyst can investigate data characteristics such as trends and outliers. We present a categorization of beneficial combinations of attributes in 2D scatterplots: (a) kth vs. (k+1)th statistical moment of a traditional or robust estimate, (b) traditional vs. robust version of the same moment, (c) two different robust estimates of the same moment. We propose selected view transformations to iteratively construct this multitude of informative views as well as to enhance the depiction of the statistical properties in scatterplots and quantile plots. In the framework, we interrelate the original distributional data and the aggregated statistics, which allows the analyst to work with both data representations simultaneously. We demonstrate our approach in the context of two visual analysis scenarios of multi-run climate simulations.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01697.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleBrushing Moments in Interactive Visual Analysisen_US
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