PROJECT TITLE :
AmbiguityVis: Visualization of Ambiguity in Graph Layouts
Node-link diagrams offer an intuitive means to explore networks and have galvanized a large number of automated graph layout methods that optimize aesthetic criteria. However, any explicit drawing approach cannot totally satisfy of these criteria simultaneously, manufacturing drawings with visual ambiguities that may impede the understanding of network structure. To bring attention to those doubtless problematic areas gift in the drawing, this paper presents a method that highlights common varieties of visual ambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguity in edge bundling and metanodes. Metrics, together with newly proposed metrics for abnormal edge lengths, visual overlap in community structures and node/edge aggregation, are proposed to quantify areas of ambiguity in the drawing. These metrics and others are then displayed using a heatmap-based visualization that has visual feedback to developers of graph drawing and visualization approaches, allowing them to quickly determine misleading areas. The novel metrics and therefore the heatmap-based mostly visualization permit a user to explore ambiguities in graph layouts from multiple perspectives in order to make cheap graph layout selections. The effectiveness of the technique is demonstrated through case studies and professional reviews.
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