Toward visual interactive exploration of heterogeneous graphs

An interesting class of heterogeneous datasets, encountered for instance in data journalism applications, results from the interconnection of data sources of different data models, ranging from very structured (e.g., relational or graphs) to semistructured (e.g., JSON, HTML, XML) to completely unstructured (text). Such heterogeneous graphs can be exploited e.g., by keyword search, to uncover connection between search keywords [1]. In this paper, we present a vision toward making such graphs easily comprehensible by human users, such as journalists seeking to understand and explore them. Our proposal is twofold: (i) abstracting the graph by recognizing structured entities; this simplifies the graph without information loss; (ii) relying on data visualization techniques to help users grasp the graph contents. Our work in this area continues; we present preliminary encouraging results.