CGV - An interactive graph visualization system. Previous work on graph visualization has yielded a wealth of efficient graph analysis algorithms and expressive visual mappings. To support the visual exploration of graph structures, a high degree of interactivity is required as well. We present a fully implemented graph visualization system, called CGV (Coordinated Graph Visualization), whose particular emphasis is on interaction. The system incorporates several interactive views that address different aspects of graph visualization. To support different visualization tasks, view ensembles can be created dynamically with the help of a flexible docking framework. Several novel techniques, including enhanced dynamic filtering, graph lenses, and edge-based navigation are presented. The main graph canvas interactions are augmented with several visual cues, among which the infinite grid and the radar view are novel. CGV provides a history mechanism that allows for undo/redo of interaction. CGV is a general system with potential application in many scenarios. It has been designed as a dual-use system that can run as a stand-alone application or as an applet in a web browser. CGV has been used to evaluate graph clustering results, to navigate topological structures of neuronal systems, and to perform analysis of some time-varying graphs.
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen: Unified functional network and nonlinear time series analysis for complex systems science: the pyunicorn package (2015)
- Jonathan F. Donges, Jobst Heitzig, Boyan Beronov, Marc Wiedermann, Jakob Runge, Qing Yi Feng, Liubov Tupikina, Veronika Stolbova, Reik V. Donner, Norbert Marwan, Henk A. Dijkstra, J. Kurths: Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package (2015) arXiv
- John, Mathias; Schulz, Hans-Jörg; Schumann, Heidrun; Uhrmacher, Adelinde M.; Unger, Andrea: Constructing and visualizing chemical reaction networks from pi-calculus models (2013)