Comparative visualization of ensembles using ensemble surface slicing

Abstract

By definition, an ensemble is a set of surfaces or volumes derived from a series of simulations or experiments. Sometimes the series is run with different initial conditions for one parameter to determine parameter sensitivity. The understanding and identification of visual similarities and differences among the shapes of members of an ensemble is an acute and growing challenge for researchers across the physical sciences. More specifically, the task of gaining spatial understanding and identifying similarities and differences between multiple complex geometric data sets simultaneously has proved challenging. This paper proposes a comparison and visualization technique to support the visual study of parameter sensitivity. We present a novel single-image view and sampling technique which we call Ensemble Surface Slicing (ESS). ESS produces a single image that is useful for determining differences and similarities between surfaces simultaneously from several data sets. We demonstrate the usefulness of ESS on two real-world data sets from our collaborators.

Future challenges for ensemble visualization

“…A sample image of their technique is shown in Figure 2. In three dimensions, slicing can help create an impression of di↵erences in isosurfaces, as demonstrated by Alabi et al [1] and shown in Figure 3. As you can see, even simple tasks such as rendering spaghetti plots becomes a visualization challenge in three dimensions.…”

Screen-space silhouettes for visualizing ensembles of 3D isosurfaces

“…Several methods have been proposed to visualize isosurfaces extracted from 3D ensemble data, e.g., by means of animation [6], volume rendering [11,44], or confidence envelopes [35,37,48]. Other methods aim at rendering multiple isosurfaces into a single 3D view [1,8]. However, only a few ensemble members can be visualized simultaneously due to cluttering and occlusion.…”

Making Sense of Scientific Simulation Ensembles With Semantic Interaction

“…On the other hand, ensemble space visual analytic tools have been developed with different levels of complexity. The least complex tool shows a side‐by‐side comparison of 3D surfaces [AWH*12]. Increasing in complexity, we see the use of pairwise sequential animation and screen door tinting to show the differences between ensemble members using value changes to field points [PPA*12], the comparison of 2D function ensembles on three levels of details (i.e.…”