IPFViewer a visual analysis system for hierarchical ensemble data

Analyzing ensemble data is very challenging due to the complexity of the task. In this paper, we describe IPFViewer, a visual analysis system for ensemble data, that is hierarchical, multidimensional and multimodal. The exemplary data set comes from a steel production facility and comprises data about their melting charges, samples and defects. Our system differs from existing ones in that it encourages the usage of side-by-side visualization of ensemble members. Besides trend analysis, outlier detection and visual exploration, side-by-side visualization of detailed ensemble members enables rapid checking for repeatability of single ensemble member analysis results. IPFViewer supports the following data interaction methods: Hierarchical sorting and filtering, reference data selection, automatic percentile selection and ensemble member aggregation, while the focus for visualization is on small multiples of multiple views.