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 language | English |
|---|---|
| Title of host publication | DL 2020 - Description Logics 2020 |
| Subtitle of host publication | Proceedings of the 33rd International Workshop on Description Logics (DL 2020) co-located with the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020) Online, September 12th to 14th, 2020 |
| Editors | S. Borgwardt, T. Meyer |
| Publisher | CEUR Workshop Proceedings |
| Pages | 1-15 |
| Number of pages | 15 |
| Publication status | Published - 2020 |
| Externally published | Yes |
| Event | 33rd International Workshop on Description Logics, DL 2020 - Virtual, Online, Greece Duration: 12 Sept 2020 → 14 Sept 2020 |
Publication series
| Name | CEUR Workshop Proceedings |
|---|---|
| Volume | 2663 |
| ISSN (Print) | 1613-0073 |
Conference
| Conference | 33rd International Workshop on Description Logics, DL 2020 |
|---|---|
| Country/Territory | Greece |
| City | Virtual, Online |
| Period | 12/09/20 → 14/09/20 |
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).
| Funders | Funder number |
|---|---|
| Deutsche Forschungsgemeinschaft | GRK 1763, 389792660 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
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