Datalog Rewritability of Disjunctive Datalog Programs and its Applications to Ontology Reasoning

Authors

  • Mark Kaminski University of Oxford
  • Yavor Nenov University of Oxford
  • Bernardo Cuenca Grau University of Oxford

DOI:

https://doi.org/10.1609/aaai.v28i1.8854

Keywords:

knowledge representation and reasoning, ontologies, datalog rewritability, disjunctive datalog, query answering, description logics, OWL 2

Abstract

We study the problem of rewriting a disjunctive datalog program into plain datalog. We show that a disjunctive program is rewritable if and only if it is equivalent to a linear disjunctive program, thus providing a novel characterisation of datalog rewritability. Motivated by this result, we propose weakly linear disjunctive datalog -- a novel rule-based KR language that extends both datalog and linear disjunctive datalog and for which reasoning is tractable in data complexity. We then explore applications of weakly linear programs to ontology reasoning and propose a tractable extension of OWL 2 RL with disjunctive axioms. Our empirical results suggest that many non-Horn ontologies can be reduced to weakly linear programs and that query answering over such ontologies using a datalog engine is feasible in practice.

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Published

2014-06-21

How to Cite

Kaminski, M., Nenov, Y., & Cuenca Grau, B. (2014). Datalog Rewritability of Disjunctive Datalog Programs and its Applications to Ontology Reasoning. Proceedings of the AAAI Conference on Artificial Intelligence, 28(1). https://doi.org/10.1609/aaai.v28i1.8854

Issue

Section

AAAI Technical Track: Knowledge Representation and Reasoning