Ontology-Mediated Query Answering for Key-Value Stores

Meghyn Bienvenu 1 Pierre Bourhis 2 Marie-Laure Mugnier 1 Sophie Tison 3 Federico Ulliana 1
1 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
2 LINKS - Linking Dynamic Data
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : We propose a novel rule-based ontology language for JSON records and investigate its computational properties. After providing a natural translation into first-order logic, we identify relationships to existing ontology languages , which yield decidability of query answering but only rough complexity bounds. By establishing an interesting and non-trivial connection to word rewriting, we are able to pinpoint the exact combined complexity of query answering in our framework and obtain tractability results for data complexity. The upper bounds are proven using a query reformu-lation technique, which can be implemented on top of key-value stores, thereby exploiting their querying facilities.
Keywords : ontology
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Conference papers
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01632090
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Submitted on : Thursday, November 9, 2017 - 6:39:34 PM
Last modification on : Friday, March 22, 2019 - 1:34:44 AM
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Meghyn Bienvenu, Pierre Bourhis, Marie-Laure Mugnier, Sophie Tison, Federico Ulliana. Ontology-Mediated Query Answering for Key-Value Stores. IJCAI: International Joint Conference on Artificial Intelligence, Aug 2017, Melbourne, Australia. ⟨lirmm-01632090⟩

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