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RDF graph summarization for first-sight structure discovery

Abstract : To help users get familiar with large RDF graphs, RDF summarization techniques can be used. In this work, we study quotient summaries of RDF graphs, that is: graph summaries derived from a notion of equivalence among RDF graph nodes. We make the following contributions: (i) four novel summaries which are often small and easy-to-comprehend, in the style of E--R diagrams; (ii) efficient (amortized linear-time) algorithms for computing these summaries either from scratch, or incrementally, reflecting additions to the graph; (iii) the first formal study of the interplay between RDF graph saturation in the presence of an RDFS ontology, and summarization; we provide a sufficient condition for a highly efficient shortcut method to build the quotient summary of a graph without saturating it; (iv) formal results establishing the shortcut conditions for some of our summaries and others from the literature; (v) experimental validations of our claim within a tool available online.
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Submitted on : Monday, August 24, 2020 - 11:04:15 AM
Last modification on : Saturday, August 29, 2020 - 3:09:52 AM

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François Goasdoué, Pawel Guzewicz, Ioana Manolescu. RDF graph summarization for first-sight structure discovery. The VLDB Journal, Springer, 2020, 29 (5), pp.1191-1218. ⟨10.1007/s00778-020-00611-y⟩. ⟨hal-02530206v2⟩

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