Triplifying equivalence set graphs

Luigi Asprino, Wouter Beek, Paolo Ciancarini, Frank van Harmelen, Valentina Presutti

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In order to conduct large-scale semantic analyses, it is necessary to calculate the deductive closure of very large hierarchical structures. Unfortunately, contemporary reasoners cannot be applied at this scale, unless they rely on expensive hardware such as a multi-node in-memory cluster. In order to handle large-scale semantic analyses on commodity hardware such as regular laptops we introduced [1] a novel data structure called Equivalence Set Graph (ESG). An ESG allows to specify compact views of large RDF graphs thus easing the accomplishment of statistical observations like the number of concepts defined in a graph, the shape of ontological hierarchies etc. ESGs are built by a procedure presented in [1] that delivers graphs as a set of maps storing nodes and edges. In this demo paper (i) we show how facts entailed by an ESG and the graph itself can be specified in RDF following a novel introduced ontology; and, (ii) we present two datasets resulting from the triplification of two ESG graphs (one for classes and one for properties).

Original languageEnglish
Title of host publicationISWC 2019 Satellites
Subtitle of host publication Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019), Auckland, New Zealand, October 26-30, 2019
EditorsMari Carmen Suárez-Figueroa, Gong Cheng, Anna Lisa Gentile, Christophe Guéret, Maria Keet, Abraham Bernstein
Number of pages4
Publication statusPublished - Oct 2019
Event2019 ISWC Satellite Tracks (Posters and Demonstrations, Industry, and Outrageous Ideas), ISWC 2019-Satellites - Auckland, New Zealand
Duration: 26 Oct 201930 Oct 2019

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR Workshop Proceedings
ISSN (Print)1613-0073


Conference2019 ISWC Satellite Tracks (Posters and Demonstrations, Industry, and Outrageous Ideas), ISWC 2019-Satellites
Country/TerritoryNew Zealand


  • Empirical Semantics
  • Linked Open Data
  • Semantic Web


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