Visual Analysis of Multi-Parameter Distributions Across Ensembles of 3D Fields

• Published in: IEEE transactions on visualization and computer graphics 2022-10, Vol.28 (10), p.3530-3545
• Main Authors: Kumpf, Alexander, Stumpfegger, Josef, Hartl, Patrick Fabian, Westermann, Rudiger
• Format: Article
• Language: English
• Subjects: 3D rendering; Data points; Data visualization; distribution comparison; Ensemble visualization; Isosurfaces; Mathematical analysis; multi-parameter visualization; parallel coordinates; Parameters; Rendering (computer graphics); Spatial distribution; Three-dimensional displays; Uncertainty; Visual analytics; Workflow
• ISSN: 1077-2626; 1941-0506
• DOI: 10.1109/TVCG.2021.3061925

For an ensemble of 3D multi-parameter fields, we present a visual analytics workflow to analyse whether and which parts of a selected multi-parameter distribution is present in all ensemble members. Supported by a parallel coordinate plot, a multi-parameter brush is applied to all ensemble members to select data points with similar multi-parameter distribution. By a combination of spatial sub-division and a covariance analysis of partitioned sub-sets of data points, a tight partition in multi-parameter space with reduced number of selected data points is obtained. To assess the representativeness of the selected multi-parameter distribution across the ensemble, we propose a novel extension of violin plots that can show multiple parameter distributions simultaneously. We investigate the visual design that effectively conveys (dis-)similarities in multi-parameter distributions, and demonstrate that users can quickly comprehend parameter-specific differences regarding distribution shape and representativeness from a side-by-side view of these plots. In a 3D spatial view, users can analyse and compare the spatial distribution of selected data points in different ensemble members via interval-based isosurface raycasting. In two real-world application cases we show how our approach is used to analyse the multi-parameter distributions across an ensemble of 3D fields.