Uncertainty-Oriented Ensemble Data Visualization and Exploration using Variable Spatial Spreading
Mingdong Zhang, Li Chen, Quan Li, Xiaoru Yuan, Junhai Yong

TL;DR
This paper introduces a novel interactive framework for ensemble data visualization that emphasizes variable spatial spreading to better explore and understand uncertainties in simulation data.
Contribution
It proposes a new uncertainty calculation method based on variable spatial spreading and designs an interactive analysis framework with multiple visualization views for flexible data exploration.
Findings
Effective uncertainty perception through new visualization views
Enhanced region and temporal analysis capabilities
Positive expert feedback on framework usability
Abstract
As an important method of handling potential uncertainties in numerical simulations, ensemble simulation has been widely applied in many disciplines. Visualization is a promising and powerful ensemble simulation analysis method. However, conventional visualization methods mainly aim at data simplification and highlighting important information based on domain expertise instead of providing a flexible data exploration and intervention mechanism. Trial-and-error procedures have to be repeatedly conducted by such approaches. To resolve this issue, we propose a new perspective of ensemble data analysis using the attribute variable dimension as the primary analysis dimension. Particularly, we propose a variable uncertainty calculation method based on variable spatial spreading. Based on this method, we design an interactive ensemble analysis framework that provides a flexible interactive…
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