Unterstützung des Editierens von Graphen in Visuellen Repräsentationen

The goal of this thesis is to provide solutions for supporting the direct editing of graphs in visual representations for analyzing graphs. For that, a conceptual view on the user's tasks is established first. On this basis, several novel approaches to "visually edit" the different data aspects of graphs - the graph's structure and associated attribute values - are introduced. Thereby, different visual graph representations suitable for communicating the data are considered.Das Ziel der vorliegenden Dissertation ist, Lösungen zur Unterstützung des direkten Editierens von Graphen in visuellen Repräsentationen zur Analyse von Graphen bereitzustellen. Dafür wird zunächst eine konzeptuelle Sicht auf die Aufgaben des Nutzers entwickelt. Auf dieser Basis werden anschließend mehrere neue Verfahren eingeführt, welche das "visuelle Editieren" der verschiedenen Datenaspekte von Graphen - der Struktur sowie dazu assoziierte Attributwerte - ermöglichen. Dabei werden verschiedene visuelle Graphrepräsentationen berücksichtigt, welche die Daten in geeigneter Form kommunizieren

Displaying User Behavior in the Collaborative Graph Visualization System OnGraX

The visual analysis of complex networks is a challenging task in many fields, such as systems biology or social sciences. Often, various domain experts work together to improve the analysis time or the quality of the analysis results. Collaborative visualization tools can facilitate the analysis process in such situations. We propose a new web-based visualization environment which supports distributed, synchronous and asynchronous collaboration. In addition to standard collaboration features like event tracking or synchronizing, our client/server-based system provides a rich set of visualization and interaction techniques for better navigation and overview of the input network. Changes made by specific analysts or even just visited network elements are highlighted on demand by heat maps. They enable us to visualize user behavior data without affecting the original graph visualization. We evaluate the usability of the heat map approach against two alternatives in a user experiment