Near-Optimal Concentric Circles Layout

The majority of graph visualization algorithms emphasize improving the readability of graphs by focusing on various vertex and edge rendering techniques. However, revealing the global connectivity structure of a graph by identifying significant vertices is an important and useful part of any graph analytics system. Centrality measures reveal the “most important” vertices of a graph, commonly referred to as central or influential vertices. Hence, a centrality-oriented visualization may highlight these important vertices and give deep insights into graph data. This paper proposes a mathematical optimization-based clustered graph layout called Near-Optimal Concentric Circles (NOCC) layout to visualize medium to large scale-free graphs. We cluster the vertices by their betweenness values and optimally place them on concentric circles to reveal the extensive connectivity structure of the graph while achieving aesthetically pleasing layouts. Besides, we incorporate different edge rendering techniques to improve graph readability and interaction.

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