GlyphLink: An interactive visualization approach for semantic graphs

• In this paper, our contribution is to introduce a method that improves handling of topology-based tasks in semantic graphs.
• Our method consists of applying relational operations to the sets of nodes where each set belongs to a different node type.
• We propose the use of glyphs in node–link diagrams to convey underlying connectivity of aggregated nodes.

Graph analysis by data visualization involves achieving a series of topology-based tasks. When the graph data belongs to a data domain that contains multiple node and link types, as in the case of semantic graphs, topology-based tasks become more challenging. To reduce visual complexity in semantic graphs, we propose an approach which is based on applying relational operations such as selecting and joining nodes of different types. We use node aggregation to reflect the relational operations to the graph. We introduce glyphs for representing aggregated nodes. Using glyphs lets us encode connectivity information of multiple nodes with a single glyph. We also use visual parameters of the glyph to encode node attributes or type specific information. Rather than doing the operations in the data abstraction layer and presenting the user with the resulting visualization, we propose an interactive approach where the user can iteratively apply the relational operations directly on the visualization. We present the efficiency of our method by the results of a usability study that includes a case study on a subset of the International Movie Database. The results of the controlled experiment in our usability study indicate a statistically significant contribution in reducing the completion time of the evaluation tasks.

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