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OWL Reasoning: Subsumption Test Hardness and Modularity.

Nicolas Matentzoglu1, Bijan Parsia1, Uli Sattler1

  • 1Information Management Group, University of Manchester, Manchester, UK.

Journal of Automated Reasoning
|August 3, 2018
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Summary
This summary is machine-generated.

Modular reasoning in Web Ontology Language (OWL) offers a modest reduction in subsumption test hardness, but its overall impact on classification time is limited. Optimizations should consider broader benefits beyond just test hardness.

Keywords:
ModulesOWLOntologiesReasoningSubsumption testing

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Area of Science:

  • Artificial Intelligence
  • Knowledge Representation and Reasoning
  • Ontology Engineering

Background:

  • Reasoning with Description Logics (DLs), the foundation of Web Ontology Language (OWL), faces high worst-case complexity.
  • Modular reasoning, decomposing ontologies into smaller parts, is proposed to mitigate this complexity.
  • Current motivations for modular reasoning include reducing subsumption test hardness and integrating delegate reasoners.

Purpose of the Study:

  • To evaluate the practical impact of modularity as an optimization technique for OWL reasoning.
  • To assess the effect of modularity on subsumption test hardness and overall classification time.
  • To provide evidence-based conclusions on the utility of modularity for ontology reasoning optimization.

Main Methods:

  • Analysis of a collection of 330 ontologies from BioPortal.
  • Decomposition of ontologies into modules.
  • Classification of modular composites using reasoners.
  • Measurement of subsumption test hardness and classification time.

Main Results:

  • Modularity shows a generally positive effect on subsumption test hardness, with a 2-fold mean reduction in the sample.
  • The impact of subsumption testing is significant only for a small subset of ontologies.
  • Over 50% of subsumption tests showed no change in hardness, and significant differences were observed across reasoners.

Conclusions:

  • Optimizations targeting subsumption test hardness require strong motivation due to their modest overall impact on classification time.
  • Employing modularity for optimization should not solely rely on potential benefits to subsumption test hardness.
  • Further research is needed to fully understand the practical implications of modular reasoning in OWL.