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Documents authored by Keller, Patric

Document
DOI: 10.4230/OASIcs.VLUDS.2011.43
Improving Safety-Critical Systems by Visual Analysis

Authors: Yi Yang, Patric Keller, Yarden Livnat, and Peter Liggesmeyer

Published in: OASIcs, Volume 27, Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011

Abstract
The importance analysis provides a means of analyzing the contribution of potential low-level system failures to identify and assess vulnerabilities of safety-critical systems. Common approaches attempt to enhance the system safety by addressing vulnerabilities using an iterative analysis process, while considering relevant constraints, e.g., cost, for optimizing the improvements. Typically, data regarding the analysis process is presented across several views with few interactive associations among them. Consequently, this hampers the identification of meaningful information supporting the decision making process. In this paper, we propose a visualization system that visually supports engineers in identifying proper solutions. The visualization integrates a decision tree with a plot representing the cause-effect relationship between the improvement ideas of vulnerabilities and the resulting risk reduction of system. Associating a component fault tree view with the plot allows to maintain helpful context information. The introduced visualization approach enables system and safety engineers to identify and analyze optimal solutions facilitating the improvement of the overall system safety.
Cite as

Yi Yang, Patric Keller, Yarden Livnat, and Peter Liggesmeyer. Improving Safety-Critical Systems by Visual Analysis. In Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011. Open Access Series in Informatics (OASIcs), Volume 27, pp. 43-58, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{yang_et_al:OASIcs.VLUDS.2011.43,
  author =	{Yang, Yi and Keller, Patric and Livnat, Yarden and Liggesmeyer, Peter},
  title =	{{Improving Safety-Critical Systems by Visual Analysis}},
  booktitle =	{Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011},
  pages =	{43--58},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-46-0},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{27},
  editor =	{Garth, Christoph and Middel, Ariane and Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2011.43},
  URN =		{urn:nbn:de:0030-drops-37406},
  doi =		{10.4230/OASIcs.VLUDS.2011.43},
  annote =	{Keywords: fault tree analysis, importance and sensitivity analysis, information vi- sualization, decision tree, safety analysis}
}
Document
DOI: 10.4230/OASIcs.VLUDS.2011.151
A General Introduction To Graph Visualization Techniques

Authors: Raga'ad M. Tarawaneh, Patric Keller, and Achim Ebert

Published in: OASIcs, Volume 27, Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011

Abstract
Generally, a graph is an abstract data type used to represent relations among a given set of data entities. Graphs are used in numerous applications within the field of information visualization, such as VLSI (circuit schematics), state-transition diagrams, and social networks. The size and complexity of graphs easily reach dimensions at which the task of exploring and navigating gets crucial. Moreover, additional requirements have to be met in order to provide proper visualizations. In this context, many techniques already have been introduced. This survey aims to provide an introduction on graph visualization techniques helping the reader to gain a first insight into the most fundamental techniques. Furthermore, a brief introduction about navigation and interaction tools is provided.
Cite as

Raga'ad M. Tarawaneh, Patric Keller, and Achim Ebert. A General Introduction To Graph Visualization Techniques. In Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011. Open Access Series in Informatics (OASIcs), Volume 27, pp. 151-164, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{tarawaneh_et_al:OASIcs.VLUDS.2011.151,
  author =	{Tarawaneh, Raga'ad M. and Keller, Patric and Ebert, Achim},
  title =	{{A General Introduction To Graph Visualization Techniques}},
  booktitle =	{Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011},
  pages =	{151--164},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-46-0},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{27},
  editor =	{Garth, Christoph and Middel, Ariane and Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2011.151},
  URN =		{urn:nbn:de:0030-drops-37484},
  doi =		{10.4230/OASIcs.VLUDS.2011.151},
  annote =	{Keywords: Graph Visualization, Layout Algorithms, Graph Drawing, Interaction Techniques}
}
Document
DOI: 10.4230/DFU.Vol2.SciViz.2011.129
Construction of Implicit Surfaces from Point Clouds Using a Feature-based Approach

Authors: Patric Keller, Oliver Kreylos, Eric S. Cowgill, Louise H. Kellogg, and Martin Hering-Bertram

Published in: Dagstuhl Follow-Ups, Volume 2, Scientific Visualization: Interactions, Features, Metaphors (2011)

Abstract
We present a novel feature-based approach to surface generation from point clouds in three-dimensional space obtained by terrestrial and airborne laser scanning. In a first step, we apply a multiscale clustering and classification of local point set neighborhoods by considering their geometric shape. Corresponding feature values quantify the similarity to curve-like, surface-like, and solid-like shapes. For selecting and extracting surface features, we build a hierarchical trivariate B-spline representation of this surface feature function. Surfaces are extracted with a variant of marching cubes (MC), providing an inner and outer shell that are merged into a single non-manifold surface component at the field’s ridges. By adapting the isovalue of the feature function the user may control surface topology and thus adapt the extracted features to the noise level of the underlying point cloud. User control and adaptive approximation make our method robust for noisy and complex point data.
Cite as

Patric Keller, Oliver Kreylos, Eric S. Cowgill, Louise H. Kellogg, and Martin Hering-Bertram. Construction of Implicit Surfaces from Point Clouds Using a Feature-based Approach. In Scientific Visualization: Interactions, Features, Metaphors. Dagstuhl Follow-Ups, Volume 2, pp. 129-143, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@InCollection{keller_et_al:DFU.Vol2.SciViz.2011.129,
  author =	{Keller, Patric and Kreylos, Oliver and Cowgill, Eric S. and Kellogg, Louise H. and Hering-Bertram, Martin},
  title =	{{Construction of Implicit Surfaces from Point Clouds Using a Feature-based Approach}},
  booktitle =	{Scientific Visualization: Interactions, Features, Metaphors},
  pages =	{129--143},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-26-2},
  ISSN =	{1868-8977},
  year =	{2011},
  volume =	{2},
  editor =	{Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol2.SciViz.2011.129},
  URN =		{urn:nbn:de:0030-drops-33032},
  doi =		{10.4230/DFU.Vol2.SciViz.2011.129},
  annote =	{Keywords: 3D Point Clouds, Surface Reconstruction, Implicit Surfaces}
}
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