Doctoral Thesis - A Visual Analysis System for Hierarchical Ensemble Data

Matthias Thurau

Abstract

Analyzing ensemble data is very challenging due to the complexity of the task. In this paper, I describe IPFViewer, a visual analysis system for ensemble data, that is hierarchical, multidimensional, multivariate and multimodal. That system forms the basis for my doctoral thesis. An exemplary data set comes from a steel production facility and comprises data about their melting charges, samples and defects. My 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.

References

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Paper Citation


in Harvard Style

Thurau M. (2014). Doctoral Thesis - A Visual Analysis System for Hierarchical Ensemble Data . In Doctoral Consortium - DCVISIGRAPP, (VISIGRAPP 2014) ISBN Not Available, pages 52-57


in Bibtex Style

@conference{dcvisigrapp14,
author={Matthias Thurau},
title={Doctoral Thesis - A Visual Analysis System for Hierarchical Ensemble Data},
booktitle={Doctoral Consortium - DCVISIGRAPP, (VISIGRAPP 2014)},
year={2014},
pages={52-57},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={Not Available},
}


in EndNote Style

TY - CONF
JO - Doctoral Consortium - DCVISIGRAPP, (VISIGRAPP 2014)
TI - Doctoral Thesis - A Visual Analysis System for Hierarchical Ensemble Data
SN - Not Available
AU - Thurau M.
PY - 2014
SP - 52
EP - 57
DO -