Background Knowledge in Ontology Matching: A Survey

Tracking #: 3085-4299

Jan Portisch
Michael Hladik
Heiko Paulheim

Responsible editor: 
Jérôme Euzenat

Submission type: 
Survey Article
Ontology matching is an integral part for establishing semantic interoperability. One of the main challenges within the ontology matching operation is semantic heterogeneity, i.e. modeling differences between the two ontologies that are to be integrated. The semantics within most ontologies or schemas are, however, typically incomplete because they are designed within a certain context which is not explicitly modeled. Therefore, external background knowledge plays a major role in the task of (semi-) automated ontology and schema matching. In this survey, we introduce the reader to the general ontology matching problem. We review the background knowledge sources as well as the approaches applied to make use of external knowledge. Our survey covers all ontology matching systems that have been presented within the years 2004 -- 2021 at a well-known ontology matching competition together with systematically selected publications in the research field. We present a classification system for external background knowledge, concept linking strategies, as well as for background knowledge exploitation approaches. We provide extensive examples and classify all ontology matching systems under review in a resource/strategy matrix obtained by coalescing the two classification systems. Lastly, we outline interesting and yet underexplored research directions of applying external knowledge within the ontology matching process.
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Review #1
Anonymous submitted on 10/Apr/2022
Review Comment:

The authors have carefully revised and provided an answer to all my concerns. In particular:

- they added a third search parameter ("ontology mapping") and extended the survey accordingly, providing the updated figures
- they clarified all issues concerning the scope of the survey (schema vs. ontology matching)
- they removed the section on evaluation metrics as it did not bring so much to the paper
- tables on OAEI results have been updated in order to cover also the results from OAEI 2021

The paper is now in shape for publication.
Thanks to the authors for all their efforts. Excellent job.