Title :
Graph clutter filtering based on connectivity distance and visibility
Author :
Mojzis, Jan ; Laclavik, Michal
Author_Institution :
Inst. of Inf., Bratislava, Slovakia
Abstract :
Graphs are often used to visualize relations between entities. Based on edges or vertices count, visualization of dense graphs can be problematic and create cluttered graphs. Many visualization methods exist to reduce visual clutter in graphs, from graph clustering or partitioning, edge bundling, filtering, by using specific layouts, lenses, colors or transparency or 3D visualizations. We present a new graph clutter filtering method, based on connectivity distance and visibility. In the comparison to current methods, we focus mainly on interconnections between already visualized vertices. Our method can significantly filter graph clutter. Although the rule of visibility may not be sufficient enough, in order to filter graph clutter, another new filter rule can be easily included, as we show. Our connection and visibility rules do not create any new edges or clusters in the graph in comparison to edge bundling or clustering methods. In order to demonstrate the effect of our method, we discuss several example visualizations.
Keywords :
data visualisation; graph colouring; information filtering; pattern clustering; 3D visualizations; connectivity distance; dense graph visualization method; edge bundling; graph clustering; graph clutter filtering; graph partitioning; visibility rules; visual clutter reduction; visualized vertices; Clutter; Color; Data visualization; Image color analysis; Layout; Lenses; Visualization; clutter reduction; connection filter; graph filtering; graph visualization;
Conference_Titel :
Science and Information Conference (SAI), 2014
Conference_Location :
London
Print_ISBN :
978-0-9893-1933-1
DOI :
10.1109/SAI.2014.6918184