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WaterFowl: a Compact, Self-indexed and Inference-enabled Immutable RDF Store

Abstract : In this paper we present WaterFowl, a novel approach for the storage of RDF triples that addresses scalability issues through compression. The architecture of our prototype, largely based on the use of succinct data structures, enables the representation of triples in a self-indexed, compact manner without requiring decompression at query answering time. Moreover, it is adapted to efficiently support RDF and RDFS entailment regimes thanks to an optimized encoding of ontology concepts and properties that does not require a complete inference materialization or query reformulation. This approach implies to make a distinction between the terminological and the assertional components of the knowledge base early in the process of data preparation, i.e., preprocessing the data before storing it in our structures. The paper describes our system’s architecture and presents some preliminary results obtained from evaluations on different datasets.
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Contributor : Guillaume Blin Connect in order to contact the contributor
Submitted on : Thursday, February 27, 2014 - 3:59:23 PM
Last modification on : Thursday, September 29, 2022 - 2:21:15 PM

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Olivier Curé, Guillaume Blin, Dominique Revuz, David Célestin Faye. WaterFowl: a Compact, Self-indexed and Inference-enabled Immutable RDF Store. 11th European Semantic Web Conference (ESWC'14), May 2014, Anissaras, Greece. pp.302-316, ⟨10.1007/978-3-319-07443-6_21⟩. ⟨hal-00952845⟩



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