Uncertainty-aware Multidimensional Ensemble Data Visualization and Exploration
IEEE Transactions on Visualization and Computer Graphics(2015)
摘要
This paper presents an efficient visualization and exploration approach for modeling and characterizing the relationships and uncertainties in the context of a multidimensional ensemble dataset. Its core is a novel dissimilarity-preserving projection technique that characterizes not only the relationships among the mean values of the ensemble data objects but also the relationships among the distributions of ensemble members. This uncertainty-aware projection scheme leads to an improved understanding of the intrinsic structure in an ensemble dataset. The analysis of the ensemble dataset is further augmented by a suite of visual encoding and exploration tools. Experimental results on both artificial and real-world datasets demonstrate the effectiveness of our approach.
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关键词
Ensemble visualization, uncertainty quantification, uncertainty visualization, multidimensional data visualization
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