LogMap Family Participation in the OAEI 2023

Abstract

system. We present the participation of LogMap and its variants in the OAEI 2023 campaign. The LogMap project started in January 2011 with the objective of developing a scalable and logic-based ontology matching LogMap [1, 2] is an ontology matching system that (i) can eficiently match semantically rich ontologies containing tens (and even hundreds) of thousands of classes, (ii) incorporates sophisticated reasoning and repair techniques to minimise the number of logical inconsistencies ISWC 2011 paper [1] has recently been awarded the SWSA Ten-Year Award.1 [3], and (iii) provides support for user intervention during the matching process [4]. LogMap 1.1. LogMap variants in the 2023 campaign As in previous campaigns, in the OAEI 2023 we have participated with two additional variants: LogMapLt is a “lightweight” variant of LogMap, which essentially only applies (eficient) string matching techniques.

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CEUR

ceur-ws.org CEUR Workshop Proceedings

LogMap distributions can be easily customized through a configuration file containing the matching parameters. Please refer to http://oaei.ontologymatching.org/2023/results/ for the results of the LogMap family in the OAEI 2023 campaign. It is worth mentioning that LogMap-Bio was one of the top systems in the new Bio-ML track [ 7, 8 ].

Acknowledgments I would like to thank Bernardo Cuenca-Grau, Ian Horrocks, Alessandro Solimando, Jiaoyan Chen, Valerie Cross, Anton Morant, Yujiao Zhou, Weiguo Xia, Xi Chen, Yuan Gong, Shuo Zhang and Rob Upson, who have contributed to the LogMap project in the past.

References

[1] E. Jiménez-Ruiz , B. Cuenca Grau , LogMap: Logic-based and Scalable Ontology Matching , in: Int'l Sem. Web Conf. (ISWC) , 2011 , pp. 273 - 288 .

[2] E. Jiménez-Ruiz , B. Cuenca Grau , Y. Zhou , I. Horrocks , Large-scale interactive ontology matching: Algorithms and implementation , in: Europ. Conf. on Artif. Intell. (ECAI) , 2012 .

[3] A. Solimando , E. Jiménez-Ruiz , G. Guerrini, Minimizing conservativity violations in ontology alignments: Algorithms and evaluation, Knowledge and Information Systems ( 2016 ).

[4] H. Li , Z. Dragisic , D. Faria , V. Ivanova , E. Jiménez-Ruiz , P. Lambrix , C. Pesquita, User validation in ontology alignment: functional assessment and impact , Knowl. Eng. Rev . 34 ( 2019 ) e15 . URL: https://doi.org/10.1017/S0269888919000080. doi:1 0 . 1 0 1 7 / S 0 2 6 9 8 8 8 9 1 9 0 0 0 0 8 0 .

[5] N. Fridman Noy , N. H. Shah , P. L. Whetzel , B. Dai , et al., BioPortal: ontologies and integrated data resources at the click of a mouse , Nucleic Acids Research 37 ( 2009 ) 170 - 173 .

[6] X. Chen , W. Xia , E. Jiménez-Ruiz , V. Cross , Extending an ontology alignment system with bioportal: a preliminary analysis , in: Poster at Int'l Sem. Web Conf. (ISWC) , 2014 .

[7] Y. He , J. Chen , H. Dong , E. Jiménez-Ruiz , A. Hadian , I. Horrocks , Machine LearningFriendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching , in: The Semantic Web - ISWC 2022 - 21st International Semantic Web Conference, Virtual Event, October 23-27 , 2022 , Proceedings, volume 13489 of Lecture Notes in Computer Science, Springer, 2022 , pp. 575 - 591 . URL: https://doi.org/10.1007/978-3- 031 -19433-7_ 33 . doi:1 0 . 1 0 0 7 / 9 7 8 - 3 - 0 3 1 - 1 9 4 3 3 - 7 \ _ 3 3 .

[8] Y. He , J. Chen , H. Dong , E. Jiménez-Ruiz , A. Hadian , I. Horrocks , Bio-ML: Machine LearningFriendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching (Version OAEI Bio-ML 2023 ), https://doi.org/10.5281/zenodo.8193375, 2023 . URL: https://doi.org/10. 5281/zenodo.8193375. doi:1 0 . 5 2 8 1 / Z E N O D O . 8 1 9 3 3 7 5 .