Semantic Blossom Graph: A New Approach for Visual Graph Exploration

Graphs are widely used to represent relationships between entities. Indeed, their simplicity in depicting connectedness backed by a mathematical formalism, make graphs an ideal metaphor to convey relatedness between entities irrespective of the domain. However, graphs pose several challenges for visual analysis. A large number of entities or a densely connected set quickly render the graph unreadable due to clutter. Typed relationships leading to multigraphs cannot clearly be represented in hierarchical layout or edge bundling, common clutter reduction techniques. We propose a novel approach to visual analysis of complex graphs based on two metaphors: semantic blossom and selective expansion. Instead of showing the whole graph, we display only a small representative subset of nodes, each with a compressed summary of relations in a semantic blossom. Users apply selective expansion to traverse the graph and discover the subset of interest. A preliminary evaluation showed that our approach is intuitive and useful for graph exploration and provided insightful ideas for future improvements.