Visualizing proofs and the modular structure of ontologies to support ontology repair

Christian Alrabbaa, Franz Baader, Raimund Dachselt, Tamara Flemisch, Patrick Koopmann

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

The classical approach for repairing a Description Logic (DL) ontology in the sense of removing an unwanted consequence is to delete a minimal number of axioms from the ontology such that the resulting ontology no longer has the consequence. While there are automated tools for computing all possible such repairs, the user still needs to decide by hand which of the (potentially exponentially many) repairs to choose. In this paper, we argue that exploring a proof of the unwanted consequence may help us to locate other erroneous consequences within the proof, and thus allows us to make a more informed decision on which axioms to remove. In addition, we suggest that looking at the so-called atomic decomposition, which describes the modular structure of the ontology, enables us to judge the impact that removing a certain axiom has. Since both proofs and atomic decompositions of ontologies may be large, visual support for inspecting them is required. We describe a prototypical system that can visualize proofs and the atomic decomposition in an integrated visualization tool to support ontology debugging.
Original languageEnglish
Title of host publicationDL 2020 - Proceedings of the 33rd International Workshop on Description Logics, co-located with the 17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020
EditorsS. Borgwardt, T. Meyer
PublisherCEUR-WS
Volume2663
Publication statusPublished - 2020
Externally publishedYes
Event33rd International Workshop on Description Logics, DL 2020 - Virtual, Online, Greece
Duration: 12 Sept 202014 Sept 2020

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073

Conference

Conference33rd International Workshop on Description Logics, DL 2020
Country/TerritoryGreece
CityVirtual, Online
Period12/09/2014/09/20

Funding

Acknowledgements. This work was partially supported by DFG grant 389792660 as part of TRR 248 (https://perspicuous-computing.science), and the DFG Research Training Group QuantLA, GRK 1763 (https://lat.inf.tu-dresden. de/quantla).

FundersFunder number
Deutsche ForschungsgemeinschaftGRK 1763, 389792660

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