Revising Ontologies via Models: The ALC-formula Case

TL;DR

This paper introduces a novel approach for updating description logic ontologies by focusing on models rather than axioms, aiming to minimally alter the ontology while effectively resolving inconsistencies, especially in automated ontology refinement scenarios.

Contribution

It proposes a new model-based framework for ontology revision, specifically instantiated for ALC-formulae, diverging from traditional axiom-based methods.

Findings

Developed general operations for model-based ontology updates

Applied the approach specifically to ALC-formulae

Ensured minimal information loss during revisions

Abstract

Most approaches for repairing description logic (DL) ontologies aim at changing the axioms as little as possible while solving inconsistencies, incoherences and other types of undesired behaviours. As in Belief Change, these issues are often specified using logical formulae. Instead, in the new setting for updating DL ontologies that we propose here, the input for the change is given by a model which we want to add or remove. The main goal is to minimise the loss of information, without concerning with the syntactic structure. This new setting is motivated by scenarios where an ontology is built automatically and needs to be refined or updated. In such situations, the syntactical form is often irrelevant and the incoming information is not necessarily given as a formula. We define general operations and conditions on which they are applicable, and instantiate our approach to the case of ALC-formulae.