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Toward Visual Interactive Exploration of Heterogeneous Graphs

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Ioana Manolescu
Emmanuel Pietriga
Fabian M Suchanek


An interesting class of heterogeneous datasets, encountered for instance in data journalism applications, results from the inter-connection 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.
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hal-02468778 , version 1 (06-02-2020)


  • HAL Id : hal-02468778 , version 1


Irène Burger, Ioana Manolescu, Emmanuel Pietriga, Fabian M Suchanek. Toward Visual Interactive Exploration of Heterogeneous Graphs. SEAdata 2020 - Workshop on Searching, Exploring and Analyzing Heterogeneous Data in conjunction with EDBT/ICDT, Mar 2020, Copenhagen, Denmark. ⟨hal-02468778⟩
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