Authors:
Matthias Thurau
;
Christoph Buck
and
Wolfram Luther
Affiliation:
University of Duisburg-Essen, Germany
Keyword(s):
Small Multiples, Coordinated Multiple Views, Ensemble Data, Trend Analysis.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
Coordinated and Multiple Views
;
General Data Visualization
;
Information and Scientific Visualization
;
Spatial Data Visualization
;
Uncertainty Visualization
;
Visual Data Analysis and Knowledge Discovery
;
Visualization Tools and Systems for Simulation and Modeling
Abstract:
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.