Incremental structural summarization of RDF graphs.

EDBT(2019)

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摘要
Realizing the full potential of Linked Open Data sharing and reuse is currently limited by the difficulty users have when trying to understand the data modeled within an RDF graph, in order to determine whether or not it may be useful for their need. We demonstrate our RDFQuotient tool, which builds compact summaries of heterogeneous RDF graphs for the purpose of first-sight visualizations. An RDFQuotient summary provides an overview of the complete structure of an RDF graph, while being typically many orders of magnitude smaller, thus can be easily grasped by new users. Our summarization algorithms are time linear in the size of the input graph and incremental: they incrementally update a summary upon addition of new data. For the demo, we plan to show the visualizations of our summaries obtained from well-known synthetic and real data sets. Further, attendees will be able to add data to the summarized RDF graphs and visually witness the incurred changes.
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