From Horn-SRIQ to Datalog: A Data-Independent Transformation That Preserves Assertion Entailment

Authors

  • David Carral TU Dresden
  • Larry González TU Dresden
  • Patrick Koopmann TU Dresden

DOI:

https://doi.org/10.1609/aaai.v33i01.33012736

Abstract

Ontology-based access to large data-sets has recently gained a lot of attention. To access data efficiently, one approach is to rewrite the ontology into Datalog, and then use powerful Datalog engines to compute implicit entailments. Existing rewriting techniques support Description Logics (DLs) from ELH to Horn-SHIQ. We go one step further and present one such data-independent rewriting technique for Horn-SRIQ, the extension of Horn-SHIQ that supports role chain axioms, an expressive feature prominently used in many real-world ontologies. We evaluated our rewriting technique on a large known corpus of ontologies. Our experiments show that the resulting rewritings are of moderate size, and that our approach is more efficient than state-of-the-art DL reasoners when reasoning with data-intensive ontologies.

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Published

2019-07-17

How to Cite

Carral, D., González, L., & Koopmann, P. (2019). From Horn-SRIQ to Datalog: A Data-Independent Transformation That Preserves Assertion Entailment. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 2736-2743. https://doi.org/10.1609/aaai.v33i01.33012736

Issue

Section

AAAI Technical Track: Knowledge Representation and Reasoning