3 research outputs found

    Explorative Graph Visualization

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    Netzwerkstrukturen (Graphen) sind heutzutage weit verbreitet. Ihre Untersuchung dient dazu, ein besseres Verständnis ihrer Struktur und der durch sie modellierten realen Aspekte zu gewinnen. Die Exploration solcher Netzwerke wird zumeist mit Visualisierungstechniken unterstützt. Ziel dieser Arbeit ist es, einen Überblick über die Probleme dieser Visualisierungen zu geben und konkrete Lösungsansätze aufzuzeigen. Dabei werden neue Visualisierungstechniken eingeführt, um den Nutzen der geführten Diskussion für die explorative Graphvisualisierung am konkreten Beispiel zu belegen.Network structures (graphs) have become a natural part of everyday life and their analysis helps to gain an understanding of their inherent structure and the real-world aspects thereby expressed. The exploration of graphs is largely supported and driven by visual means. The aim of this thesis is to give a comprehensive view on the problems associated with these visual means and to detail concrete solution approaches for them. Concrete visualization techniques are introduced to underline the value of this comprehensive discussion for supporting explorative graph visualization

    Combining DagMaps and Sugiyama Layout for the Navigation of Hierarchical Data

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    International audienceThis paper presents a novel technique for exploring and navigating large hierarchies, not restricted to trees but to directed acyclic graphs (DAGs). The technique combines two different visualizations emphasizing different points of view the user can adopt when analyzing the content of the hierarchy. Usual hierarchical (node-link) layout reflect the relative position of nodes in the hierarchy while a variation of a treemap emphasizes node attributes. The classical treemap algorithm has been adapted in order to deal with DAGs. Linking the two views enables the user to visually and interactively explore elements of the hierarchy with respect to selected attributes, while being able to locate the node in the DAG
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