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Brushing Moments in Interactive Visual Analysis
Author(s) -
Kehrer Johannes,
Filzmoser Peter,
Hauser Helwig
Publication year - 2010
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2009.01697.x
Subject(s) - outlier , computer science , moment (physics) , kurtosis , categorization , skewness , context (archaeology) , variance (accounting) , computational statistics , quantile , data mining , artificial intelligence , machine learning , statistics , mathematics , geography , physics , accounting , archaeology , classical mechanics , business
We 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) k th 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.