Abstract

The construction and maintenance of ontologies is an error-prone task. As such, it is not uncommon to detect unwanted or erroneous consequences in large-scale ontologies which are already deployed in production. While waiting for a corrected version, these ontologies should still be available for use in a “safe” manner, which avoids the known errors. At the same time, the knowledge engineer in charge of producing the new version requires support to explore only the potentially problematic axioms, and reduce the number of exploration steps. In this paper, we explore the problem of deriving meaningful consequences from ontologies which contain known errors. Our work extends the ideas from inconsistency-tolerant reasoning to allow for arbitrary entailments as errors, and allows for any part of the ontology (be it the terminological elements or the facts) to be the causes of the error. Our study shows that, with a few exceptions, tasks related to this kind of reasoning are intractable in general, even for very inexpressive description logics.

Highlights

  • Description logics (DLs) [4] are a family of knowledge representation formalisms, which have been successfully applied to build large ontologies modelling different application domains

  • For this paper we focus on the lightweight families of description logics, which are known as the DL-Lite and EL families, using a meaningful representative of each family

  • We have studied the problem of dealing with and managing errors in lightweight description logic ontologies

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Summary

Introduction

Description logics (DLs) [4] are a family of knowledge representation formalisms, which have been successfully applied to build large ontologies modelling different application domains. It should still be possible to use this ontology, applying a “safe” mode that tries to avoid the (potential) causes for the known error. At the end of the paper, we study the extra-logical problem of helping the knowledge engineer in finding the wrong axioms which caused the error in the first place. We suggest finding an axiom that divides the number of potential repairs in half according to its membership in them, but show that even this task is hard for very simple logics. This paper collects, corrects, and improves results which have been previously presented at conferences [20, 22, 23]

Preliminaries
Error‐Tolerant Reasoning
IAR Repairs
Conclusions
Full Text
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