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https://ceur-ws.org/Vol-3063/om2021_preface.pdf
Ontology Matching
OM-2021
Proceedings of the ISWC Workshop
Introduction
Ontology matching1 is a key interoperability enabler for the semantic web, as well as a
useful tactic in some classical data integration tasks dealing with the semantic hetero-
geneity problem. It takes ontologies as input and determines as output an alignment,
that is, a set of correspondences between the semantically related entities of those on-
tologies. These correspondences can be used for various tasks, such as ontology merg-
ing, data interlinking, query answering or navigation over knowledge graphs. Thus,
matching ontologies enables the knowledge and data expressed with the matched on-
tologies to interoperate.
The workshop had three goals:
• To bring together leaders from academia, industry and user institutions to assess
how academic advances are addressing real-world requirements. The workshop
strives to improve academic awareness of industrial and final user needs, and
therefore, direct research towards those needs. Simultaneously, the workshop
serves to inform industry and user representatives about existing research efforts
that may meet their requirements. The workshop also investigated how the on-
tology matching technology is going to evolve.
• To conduct an extensive and rigorous evaluation of ontology matching and in-
stance matching (link discovery) approaches through the OAEI (Ontology Align-
ment Evaluation Initiative) 2021 campaign2 .
• To examine similarities and differences from other, old, new and emerging, tech-
niques and usages, such as process matching, web table matching or knowledge
embeddings.
The program committee selected 5 submissions for oral presentation and 6 submis-
sions for poster presentation. 20 matching systems participated in this year’s OAEI
campaign. Further information about the Ontology Matching workshop can be found
at: http://om2021.ontologymatching.org/.
1 http://www.ontologymatching.org/
2 http://oaei.ontologymatching.org/2021
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Acknowledgments. We thank all members of the program committee, authors and
local organizers for their efforts. We appreciate support from Trentino Digitale3 , the
EU SEALS (Semantic Evaluation at Large Scale) project4 , the EU HOBBIT (Holistic
Benchmarking of Big Linked Data) project5 , the MELT (Matching EvaLuation Toolkit)
project6 , the Pistoia Alliance Ontologies Mapping project7 , IBM Research8 and SIR-
IUS Centre for Scalable Data Access9 .
Pavel Shvaiko
Jérôme Euzenat
Ernesto Jiménez-Ruiz
Oktie Hassanzadeh
Cássia Trojahn
December 2021
3 www.trentinodigitale.it
4 www.seals-project.eu
5 https://project-hobbit.eu/challenges/om2020/
6 https://dwslab.github.io/melt/
7 www.pistoiaalliance.org/projects/current-projects/ontologies-mapping
8 research.ibm.com
9 https://www.mn.uio.no/sirius/
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Organization
Organizing Committee
Pavel Shvaiko,
Trentino Digitale SpA, Italy
Jérôme Euzenat,
INRIA & University Grenoble Alpes, France
Ernesto Jiménez-Ruiz,
City, University of London, UK & SIRIUS, University of Oslo, Norway
Oktie Hassanzadeh,
IBM Research, USA
Cássia Trojahn,
IRIT, France
Program Committee
Alsayed Algergawy, Jena University, Germany
Manuel Atencia, INRIA & University Grenoble Alpes & INRIA, France
Zohra Bellahsene, LIRMM, France
Jiaoyan Chen, University of Oxford, UK
Valerie Cross, Miami University, USA
Jérôme David, University Grenoble Alpes & INRIA, France
Gayo Diallo, University of Bordeaux, France
Daniel Faria, Instituto Gulbenkian de Ciéncia, Portugal
Alfio Ferrara, University of Milan, Italy
Marko Gulić, University of Rijeka, Croatia
Wei Hu, Nanjing University, China
Ryutaro Ichise, National Institute of Informatics, Japan
Antoine Isaac, Vrije Universiteit Amsterdam & Europeana, Netherlands
Naouel Karam, Fraunhofer, Germany
Prodromos Kolyvakis, EPFL, Switzerland
Patrick Lambrix, Linköpings Universitet, Sweden
Oliver Lehmberg, University of Mannheim, Germany
Fiona McNeill, Heriot Watt University, UK
Majeed Mohammadi, Eindhoven University of Technology, Netherlands
Axel Ngonga, University of Paderborn, Germany
George Papadakis, University of Athens, Greece
Catia Pesquita, University of Lisbon, Portugal
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Henry Rosales-Méndez, University of Chile, Chile
Kavitha Srinivas, IBM, USA
Pedro Szekely, University of Southern California, USA
Valentina Tamma, University of Liverpool, UK
Ludger van Elst, DFKI, Germany
Xingsi Xue, Fujian University of Technology, China
Ondřej Zamazal, Prague University of Economics, Czech Republic
Songmao Zhang, Chinese Academy of Sciences, China
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Table of Contents
Long Technical Papers
Biomedical ontology alignment with BERT
Yuan He, Jiaoyan Chen, Denvar Antonyrajah, Ian Horrocks . . . . . . . . . . . . . . . . . . . . . . 1
Matching with transformers in MELT
Sven Hertling, Jan Portisch, Heiko Paulheim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Property-based entity type graph matching
Fausto Giunchiglia, Daqian Shi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
A hybrid approach for large knowledge graphs matching
Omaima Fallatah, Ziqi Zhang, Frank Hopfgartner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Challenges of evaluating complex alignments
Beatriz Lima, Daniel Faria, Catia Pesquita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
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OAEI Papers
Results of the Ontology Alignment Evaluation Initiative 2021
Mina Abd Nikooie Pour, Alsayed Algergawy, Florence Amardeilh,
Reihaneh Amini, Omaima Fallatah, Daniel Faria, Irini Fundulaki,
Ian Harrow, Sven Hertling, Pascal Hitzler, Martin Huschka,
Liliana Ibanescu, Ernesto Jiménez-Ruiz, Naouel Karam, Amir Laadhar,
Patrick Lambrix, Huanyu Li, Ying Li, Franck Michel, Engy Nasr,
Heiko Paulheim, Catia Pesquita, Jan Portisch, Catherine Roussey,
Tzanina Saveta, Pavel Shvaiko, Andrea Splendiani, Cássia Trojahn,
Jana Vataščinová, Beyza Yaman, Ondřej Zamazal, Lu Zhou . . . . . . . . . . . . . . . . . . . . . 62
ALIN results for OAEI 2021
Jomar da Silva, Kate Revoredo, Fernanda Baião, Cabral Lima . . . . . . . . . . . . . . . . . 109
ALOD2vec matcher results for OAEI 2021
Jan Portisch, Heiko Paulheim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
AgreementMakerDeep results for OAEI 2021
Zhu Wang, Isabel F. Cruz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
AML and AMLC results for OAEI 2021
Daniel Faria, Beatriz Lima, Marta Contreiras Silva,
Francisco Couto, Catia Pesquita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
ATBox results for OAEI 2021
Sven Hertling, Heiko Paulheim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Fine-TOM matcher results for OAEI 2021
Leon Knorr, Jan Portisch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
GMap results for OAEI 2021
Weizhuo Li, Shiqi Zhou, Qiu Ji, Bingjie Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
KGMatcher results for OAEI 2021
Omaima Fallatah, Ziqi Zhang, Frank Hopfgartner . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
Lily results for OAEI 2021
Shiyi Zou, Jiajun Liu, Zherui Yang, Yunyan Hu, Peng Wang . . . . . . . . . . . . . . . . . . . . 167
LogMap family participation in the OAEI 2021
Ernesto Jiménez-Ruiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
LSMatch results for OAEI 2021
Abhisek Sharma, Archana Patel, Sarika Jain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
OTMapOnto: optimal transport-based ontology matching
Yuan An, Alex Kalinowski, Jane Greenberg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
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TOM matcher results for OAEI 2021
Daniel Kossack, Niklas Borg, Leon Knorr, Jan Portisch . . . . . . . . . . . . . . . . . . . . . . . . 193
Wiktionary matcher results for OAEI 2021
Jan Portisch, Heiko Paulheim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
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Posters
Combining FCA-Map with representation learning for aligning
large biomedical ontologies
Guoxuan Li, Songmao Zhang, Jiayi Wei, Wenqian Ye . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Integrating knowledge graphs for explainable artificial intelligence
in biomedicine
Marta Contreiras Silva, Daniel Faria, Catia Pesquita . . . . . . . . . . . . . . . . . . . . . . . . . 209
Concept for metadata and time series data integration
based on a material science application ontology
Paul Zierep, Dirk Helm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
Bootstrapping supervised product taxonomy mapping
with hierarchical path translations for the regulatory intelligence domain
Alfredo Maldonado, Spencer Sharpe, Paul ter Horst . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
State-of-the-art instance matching methods for knowledge graphs
Alex Boyko, Siamak Farshidi, Zhiming Zhao . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
ThValRec: threshold value recommendation approach for ontology matching
Kumar Vidhani, Gurpriya Bhatia, Mangesh Gharote, Sachin Lodha . . . . . . . . . . . . . 217
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