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<pre>
                         Ontology Matching
                                    OM-2019


                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
heterogeneity problem. It takes ontologies as input and determines as output an align-
ment, that is, a set of correspondences between the semantically related entities of
those ontologies. These correspondences can be used for various tasks, such as ontol-
ogy merging, data translation, query answering or navigation over knowledge graphs.
Thus, matching ontologies enables the knowledge and data expressed with the matched
ontologies 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) 2019 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 3 long and 2 short submissions for oral presenta-
tion and 7 submissions 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://om2019.ontologymatching.org/.


  1 http://www.ontologymatching.org/
  2 http://oaei.ontologymatching.org/2019


                                           i
Acknowledgments. We thank all members of the program committee, authors and
local organizers for their efforts. We appreciate support from the Trentino as a Lab3
initiative of the European Network of the Living Labs4 at Trentino Digitale5 , the EU
SEALS (Semantic Evaluation at Large Scale) project6 , the EU HOBBIT (Holistic
Benchmarking of Big Linked Data) project7 , the Pistoia Alliance Ontologies Mapping
project8 and IBM Research9 .


Pavel Shvaiko
Jérôme Euzenat
Ernesto Jiménez-Ruiz
Oktie Hassanzadeh
Cássia Trojahn

December 2019


  3 http://www.taslab.eu
  4 http://www.openlivinglabs.eu
  5 http://www.trentinodigitale.it
  6 http://www.seals-project.eu
  7 https://project-hobbit.eu/challenges/om2019/
  8 http://www.pistoiaalliance.org/projects/ontologies-mapping/
  9 research.ibm.com


                                         ii
                               Organization


Organizing Committee
Pavel Shvaiko,
Trentino Digitale SpA, Italy

Jérôme Euzenat,
INRIA & University Grenoble Alpes, France

Ernesto Jiménez-Ruiz,
City, Univeristy of London, UK & SIRIUS, Univeristy of Oslo, Norway

Oktie Hassanzadeh,
IBM Research, USA

Cássia Trojahn,
IRIT, France


Program Committee
Alsayed Algergawy, Jena University, Germany
Manuel Atencia, 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
Warith Eddine Djeddi, LIPAH & LABGED, Tunisia
AnHai Doan, University of Wisconsin, USA
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
Marouen Kachroudi, Université de Tunis El Manar, Tunis
Simon Kocbek, University of Melbourne, Australia
Prodromos Kolyvakis, EPFL, Switzerland
Patrick Lambrix, Linköpings Universitet, Sweden
Oliver Lehmberg, University of Mannheim, Germany
Vincenzo Maltese, University of Trento, Italy
Fiona McNeill, University of Edinburgh, UK
Christian Meilicke, University of Mannheim, Germany

                                       iii
Peter Mork, MITRE, USA
Andriy Nikolov, Metaphacts GmbH, Germany
Axel Ngonga, University of Paderborn, Germany
George Papadakis, University of Athens, Greece
Catia Pesquita, University of Lisbon, Portugal
Henry Rosales-Méndez, University of Chile, Chile
Juan Sequeda, data.world, USA
Kavitha Srinivas, IBM, USA
Giorgos Stoilos, National Technical University of Athens, Greece
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


                                        iv
                                          Table of Contents


Long Technical Papers

Matching ontologies for air traffic management:
a comparison and reference alignment of the AIRM and NASA ATM ontologies
Audun Vennesland, Richard M. Keller, Christoph G. Schuetz,
Eduard Gringinger, Bernd Neumayr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Multi-view embedding for biomedical ontology matching
Weizhuo Li, Xuxiang Duan, Meng Wang, XiaoPing Zhang, Guilin Qi . . . . . . . . . . . . . 13

Identifying mappings among knowledge graphs by formal concept analysis
Guowei Chen, Songmao Zhang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25


Short Technical Papers

Hypernym relation extraction for establishing subsumptions:
preliminary results on matching foundational ontologies
Mouna Kamel, Daniela Schmidt, Cássia Trojahn, Renata Vieira . . . . . . . . . . . . . . . . . 36

Generating corrupted data sources for the evaluation of matching systems
Fiona McNeill, Diana Bental, Alasdair Gray,
Sabina Jedrzejczyk, Ahmad Alsadeeqi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41


                                                            v
OAEI Papers

Results of the Ontology Alignment Evaluation Initiative 2019
Alsayed Algergawy, Daniel Faria, Alfio Ferrara, Irini Fundulaki,
Ian Harrow, Sven Hertling, Ernesto Jiménez-Ruiz, Naouel Karam,
Abderrahmane Khiat, Patrick Lambrix, Huanyu Li, Stefano Montanelli,
Heiko Paulheim, Catia Pesquita, Tzanina Saveta, Pavel Shvaiko,
Andrea Splendiani, Elodie Thiéblin, Cássia Trojahn,
Jana Vataščinová, Ondřej Zamazal, Lu Zhou . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

AnyGraphMatcher submission to the OAEI
knowledge graph challenge 2019
Alexander Lütke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

ALIN results for OAEI 2019
Jomar da Silva, Carla Delgado, Kate Revoredo, Fernanda Baião . . . . . . . . . . . . . . . . 94

AML and AMLC results for OAEI 2019
Daniel Faria, Catia Pesquita, Teemu Tervo,
Francisco M. Couto, Isabel F. Cruz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

AROA results for 2019 OAEI
Lu Zhou, Michelle Cheatham, Pascal Hitzler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

CANARD complex matching system:
results of the 2019 OAEI evaluation campaign
Elodie Thiéblin, Ollivier Haemmerlé, Cássia Trojahn . . . . . . . . . . . . . . . . . . . . . . . . . 114

DOME results for OAEI 2019
Sven Hertling, Heiko Paulheim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

EVOCROS: results for OAEI 2019
Juliana Medeiros Destro, Javier A. Vargas,
Julio Cesar dos Reis, Ricardo da S. Torres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

FCAMap-KG results for OAEI 2019
Fei Chang, Guowei Chen, Songmao Zhang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138

FTRLIM results for OAEI 2019
Xiaowen Wang, Yizhi Jiang, Yi Luo, Hongfei Fan,
Hua Jiang, Hongming Zhu, Qin Liu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146

Lily results for OAEI 2019
Jiangheng Wu, Zhe Pan, Ce Zhang, Peng Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153

LogMap family participation in the OAEI 2019
Ernesto Jiménez-Ruiz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160


                                                                   vi
ONTMAT1: results for OAEI 2019
Saida Gherbi, Mohamed Tarek Khadir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

POMap++ results for OAEI 2019:
fully automated machine learning approach for ontology matching
Amir Laadhar, Faiza Ghozzi, Imen Megdiche, Franck Ravat,
Olivier Teste, Faiez Gargouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

SANOM results for OAEI 2019
Majid Mohammadi, Amir Ahooye Atashin, Wout Hofman, Yao-Hua Tan . . . . . . . . . 175

Wiktionary matcher
Jan Portisch, Michael Hladik, Heiko Paulheim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181


                                                             vii
Posters

MultiKE: a multi-view knowledge graph embedding framework
for entity alignment
Wei Hu, Qingheng Zhang, Zequn Sun, Jiacheng Huang . . . . . . . . . . . . . . . . . . . . . . . . 189

MTab: matching tabular data to knowledge graph
with probability models
Phuc Nguyen, Natthawut Kertkeidkachorn,
Ryutaro Ichise, Hideaki Takeda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191

Generating referring expressions from knowledge graphs
Armita Khajeh Nassiri, Nathalie Pernelle, Fatiha Saı̈s . . . . . . . . . . . . . . . . . . . . . . . . . 193

Semantic table interpretation using MantisTable
Marco Cremaschi, Anisa Rula, Alessandra Siano, Flavio De Paoli . . . . . . . . . . . . . . 195

Towards explainable entity matching via comparison queries
Alina Petrova, Egor V. Kostylev, Bernardo Cuenca Grau,
Ian Horrocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

Discovering expressive rules for
complex ontology matching and data interlinking
Manuel Atencia, Jérôme David, Jérôme Euzenat, Liliana Ibanescu,
Nathalie Pernelle, Fatiha Saı̈s, Elodie Thiéblin, Cássia Trojahn . . . . . . . . . . . . . . . . 199

Decentralized reasoning on a network of aligned ontologies
with link keys
Jérémy Lhez, Chan Le Duc, Thinh Dong, Myriam Lamolle . . . . . . . . . . . . . . . . . . . . . 201


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</pre>