LogMap Family Participation in the OAEI 2022

Abstract

We present the participation of LogMap and its variants in the OAEI 2022 campaign. The LogMap project started in January 2011 with the objective of developing a scalable and logic-based ontology matching system. This is the eleventh participation in the OAEI and the experience has so far been very positive. LogMap [1, 2] is a highly scalable ontology matching system that implements the consistency and locality principles [3]. LogMap is one of the few 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, and (iii) provides support for user intervention during the matching process. LogMap ISWC 2011 paper [1] has recently been awarded the SWSA Ten-Year 1.1. LogMap variants in the 2022 campaign As in previous campaigns, in the OAEI 2022 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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Award.1 https://www.city.ac.uk/about/people/academics/ernesto-jimenez-ruiz (E. Jiménez-Ruiz)

© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings 2LogMapC (https://github.com/asolimando/logmap-conservativity/) is a variant of LogMap which, in addition to the consistency and locality principles, also implements the conservativity principle (see details in [ 7 ]).

1.2. Link to the system and parameters file

LogMap is open-source and released under the Apache-2.0 License.3 LogMap components and source code are available from the LogMap’s GitHub page: https://github.com/ ernestojimenezruiz/logmap-matcher/.

LogMap distributions can be easily customized through a configuration file containing the matching parameters.

LogMap, including support for interactive ontology matching, can also be used directly through an AJAX-based Web interface: http://krrwebtools.cs.ox.ac.uk/. This interface has been very well received by the community since it was deployed in 2012. More than 5,750 requests coming from a broad range of users have been processed so far.

We have recently developed a new interface for LogMap to enable the access to its matching capabilities as a service [ 8 ].4

1.3. LogMap as a mapping repair system

Only a very few systems participating in the OAEI competition implement repair techniques. As a result, existing matching systems (even those that typically achieve very high precision scores) compute mappings that lead in many cases to a large number of unsatisfiable classes.

We believe that these systems could significantly improve their output if they were to implement repair techniques similar to those available in LogMap. Therefore, with the goal of providing a useful service to the community, we have made LogMap’s ontology repair module (LogMap-Repair) available as a self-contained software component that can be seamlessly integrated in most existing ontology matching systems [ 9, 10 ].

1.4. LogMap as a matching task division system

LogMap also includes a novel module to divide the ontology alignment task into (independent) manageable subtasks [ 11 ]. This component relies on LogMap’s lexical index, a neural embedding model [ 12 ] and locality-based modules [ 13 ]. This module can be integrated within existing ontology alignment systems as a external module to support them complete large-scale matching tasks.

1.5. Results

Please refer to http://oaei.ontologymatching.org/2022/results/ for the results of the LogMap family in the OAEI 2022 campaign.

Acknowledgments I would also 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. 3http://www.apache.org/licenses/ 4https://github.com/rupson/knowledge-graph-alignment-as-a-service

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] E. Jiménez-Ruiz , B. Cuenca Grau , I. Horrocks , R. Berlanga , Logic-based assessment of the compatibility of UMLS ontology sources , J. Biomed. Sem . 2 ( 2011 ).

[4] 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 .

[5] A. Ghazvinian , N. F. Noy , C. Jonquet , N. H. Shah , M. A. Musen , What four million mappings can tell you about two hundred ontologies , in: Int'l Sem. Web Conf. (ISWC) , 2009 .

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

[8] R. Upson , E. Jiménez-Ruiz , Knowledge Graph Alignmnet as a Service , in: ISWC Posters & Demos , 2022 .

[9] E. Jiménez-Ruiz , C. Meilicke , B. Cuenca Grau , I. Horrocks , Evaluating mapping repair systems with large biomedical ontologies , in: 26th Description Logics Workshop , 2013 .

[10] D. Faria , E. Jiménez-Ruiz , C. Pesquita , E. Santos , F. M. Couto , Towards annotating potential incoherences in bioportal mappings , in: 13th Int'l Sem. Web Conf. (ISWC) , 2014 . doi:1 0 . 1 0 0 7 / 9 7 8 - 3 - 3 1 9 - 1 1 9 1 5 - 1 _ 2 .

[11] E. Jiménez-Ruiz , A. Agibetov , J. Chen , M. Samwald , V. Cross , Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-Based Modules , in: 24th European Conference on Artificial Intelligence (ECAI) , 2020 , pp. 784 - 791 .

[12] L. Wu , A. Fisch , S. Chopra , K. Adams , A. Bordes , J. Weston , Starspace: Embed all the things! , arXiv preprint arXiv:1709.03856 ( 2017 ).

[13] B. Cuenca Grau , I. Horrocks, Y. Kazakov , U. Sattler, Modular reuse of ontologies: Theory and practice , J. Artif. Intell. Res . 31 ( 2008 ) 273 - 318 .