The Sixteenth International Workshop on Ontology Matching

collocated with the 20th International Semantic Web Conference ISWC-2021
October 25th, 2021, to be held as a Virtual Conference due to COVID-19

Download OM-2021 proceedings: CEUR-WS Vol-3063

Objectives Call for papers Submissions Accepted papers Program Organization OM-2020


Ontology matching is a key interoperability enabler for the Semantic Web, as well as a useful technique in some classical data integration tasks dealing with the semantic heterogeneity 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 ontologies. These correspondences can be used for various tasks, such as ontology merging, data interlinking, query answering or navigation over knowledge graphs. Thus, matching ontologies enables the knowledge and data expressed with the matched ontologies to interoperate.

The workshop has three goals:
  • To bring together leaders from academia, industry and user institutions to assess how academic advances are addressing real-world requirements. The workshop will strive to improve academic awareness of industrial and final user needs, and therefore, direct research towards those needs. Simultaneously, the workshop will serve to inform industry and user representatives about existing research efforts that may meet their requirements. The workshop will also investigate how the ontology matching technology is going to evolve, especially with respect to data interlinking, process matching, web table and knowledge graph matching tasks.

  • To conduct an extensive and rigorous evaluation of ontology matching and instance matching (link discovery) approaches through the OAEI (Ontology Alignment Evaluation Initiative) 2021 campaign.

  • To examine similarities and differences from other, old, new and emerging, techniques and usages, such as process matching, web table matching or knowledge embeddings.

Call for papers


The workshop encourages participation from academia, industry and user institutions with the emphasis on theoretical and practical aspects of ontology matching. On the one side, we expect representatives from industry and user organizations to present business cases and their requirements for ontology matching. On the other side, we expect academic participants to present their approaches vis-a-vis those requirements. The workshop provides an informal setting for researchers and practitioners from different related initiatives to meet and benefit from each other's work and requirements.

This year, in sync with the main conference, we encourage submissions specifically devoted to: (i) datasets, benchmarks, software tools/services, APIs, methodologies, protocols and metrics (not necessarily related to OAEI), and (ii) application of ontology and instance matching technology in a specific domain and assessment of its usefulness to the final users.

Topics of interest include but are not limited to:

  • Business and use cases for matching (e.g., big, open, closed data)
  • Requirements to matching from specific application scenarios (e.g., public sector, homeland security)
  • Application of matching techniques in real-world scenarios (e.g., in cloud, with mobile apps)
  • Formal foundations and frameworks for matching
  • Novel matching methods, including link prediction, ontology-based data access
  • Matching and knowledge graphs
  • Matching and deep learning
  • Matching and embeddings
  • Matching and big data
  • Matching and linked data
  • Instance matching, data interlinking and relations between them
  • Privacy-aware matching
  • Process model matching
  • Large-scale and efficient matching techniques
  • Matcher selection, combination and tuning
  • User involvement (including both technical and organizational aspects)
  • Explanations in matching
  • Social and collaborative matching
  • Uncertainty in matching
  • Expressive alignments
  • Reasoning with alignments
  • Alignment coherence and debugging
  • Alignment management
  • Matching for traditional applications (e.g., data science)
  • Matching for emerging applications (e.g., web tables, knowledge graphs)

Contributions to the workshop can be made in terms of technical papers and posters/statements of interest addressing different issues of ontology matching as well as participating in the OAEI 2021 campaign. Long technical papers should be of max. 12 pages. Short technical papers should be of max. 5 pages. Posters/statements of interest should not exceed 2 pages. All contributions have to be prepared using the LNCS Style and should be submitted in PDF format (no later than August 9th, 2021) through the workshop submission site at:

Contributors to the OAEI 2021 campaign have to follow the campaign conditions and schedule at

Important dates:

  • August 9th, 2021: CLOSED
    Deadline for the submission of papers
  • September 6th, 2021: CLOSED
    Deadline for the notification of acceptance/rejection
  • September 20th, 2021: CLOSED
    Workshop camera ready copy submission
  • October 15th, 2021: CLOSED
    Early ISWC'21 registration deadline.
  • October 25th, 2021:
    OM-2021, to be held as a Virtual Conference

Contributions will be refereed by the Program Committee. Accepted papers will be published in the workshop proceedings as a volume of CEUR-WS as well as indexed on DBLP. By submitting a paper, the authors accept the CEUR-WS and DBLP publishing rules (CC-BY 4.0 license model).

Accepted Papers

Long Technical Papers:

OAEI Papers:

Abstracts (ex-posters):

CST (China) EDT (US) CEST (EU) Links Schedule
19:45-20:00 7:45-8:00 13:45-14:00 Zoom Welcome and workshop overview Organizers
20:00-20:30 8:00-8:30 14:00-14:30 Zoom Summary of the OAEI 2021 campaign and the SemTab challenge
20:30-21:30 8:30-9:30 14:30-15:30 Parallel sessions ( OAEI and Abstracts
AgreementMakerDeep results for OAEI 2021
Zhu Wang, Isabel F. Cruz
AML results for OAEI 2021
Daniel Faria, Catia Pesquita
LogMap results for OAEI 2021
Ernesto Jimenez-Ruiz
LSMatch results for OAEI 2021
Abhisek Sharma, Archana Patel, Sarika Jain
OTMapOnto: optimal transport-based ontology matching
Yuan An, Alex Kalinowski, Jane Greenberg
SemTab summary
Ernesto Jimenez-Ruiz
JenTab - SemTab
Nora Abdelmageed
Magic - SemTab
Bram Steenwinckel
MantisTable V: a novel and efficient approach to semantic table interpretation
Marco Cremaschi, Roberto Avogadro
Combining FCA-Map with representation learning for aligning large biomedical ontologies
Guoxuan Li, Songmao Zhang, Jiayi Wei, Wenqian Ye
Integrating knowledge graphs for explainable artificial intelligence in biomedicine
Marta Contreiras Silva, Daniel Faria, and Catia Pesquita
Concept for metadata and time series data integration based on a material science application ontology
Paul Zierep, Dirk Helm
Bootstrapping supervised product taxonomy mapping with hierarchical path translations for the regulatory intelligence domain
Alfredo Maldonado, Spencer Sharpe, Paul ter Horst
State-of-the-art instance matching methods for knowledge graphs
Alex Boyko, Siamak Farshidi, Zhiming Zhao
ThValRec: threshold value recommendation approach for ontology matching
Kumar Vidhani, Gurpriya Bhatia, Mangesh Gharote, Sachin Lodha
21:30-22:30 9:30-10:30 15:30-16:30 Zoom Keynote address by Wang-Chiew Tan
Deep Data Integration
Abstract: We are witnessing the widespread adoption of deep learning techniques as avant-garde solutions to different computational problems in recent years. In data integration, the use of deep learning techniques has helped establish several state-of-the-art results in long standing problems, including information extraction, entity matching, data cleaning, and table understanding. In this talk, I will reflect on the strengths of deep learning and how that has helped move forward the needle in data integration. I will also discuss a few challenges associated with solutions based on deep learning techniques and describe some opportunities for the future work.
Bio: Wang-Chiew is a research scientist at Facebook AI. Before she was the Head of Research at Megagon Labs, where she led the research efforts on building advanced technologies to enhance search by experience. This included research on data integration, information extraction, text mining and summarization, knowledge base construction and commonsense reasoning, and data visualization. Prior to joining Megagon Labs, she was a Professor of Computer Science at University of California, Santa Cruz. She also spent two years at IBM Research - Almaden.

22:30-22:50 10:30-10:50 16:30-16:50 Break
22:50-00:30 10:50-12:30 16:50-18:30 Zoom Paper presentation session: Methods and Applications
22:50-23:10 10:50-11:10 16:50-17:10 Biomedical ontology alignment with BERT
Yuan He, Jiaoyan Chen, Denvar Antonyrajah, Ian Horrocks
23:10-23:30 11:10-11:30 17:10-17:30 Matching with transformers in MELT
Sven Hertling, Jan Portisch, Heiko Paulheim
23:30-23:50 11:30-11:50 17:30-17:50 Property-based entity type graph matching
Fausto Giunchiglia, Daqian Shi
23:50-00:10 11:50-12:10 17:50-18:10 A hybrid approach for large knowledge graphs matching
Omaima Fallatah, Ziqi Zhang, Frank Hopfgartner
00:10-00:30 12:10-12:30 18:10-18:30 Challenges of evaluating complex alignments
Beatriz Lima, Daniel Faria, Catia Pesquita
00:30-00:45 12:30-12:45 18:30-18:45 Zoom Tribute to Isabel Cruz
00:45-01:30 12:45-13:30 18:45-19:30 Zoom Discussion and wrap-up

Organizing Committee:

  • Pavel Shvaiko (Main contact)
    Trentino Digitale, Italy
    E-mail: pavel [dot] shvaiko [at] tndigit [dot] it
  • Jérôme Euzenat
    INRIA & Univ. 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, INRIA & Univ. Grenoble Alpes, 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
  • Majid Mohammadi, Eindhoven University of Technology, Netherlands
  • 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
  • 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


We appreciate support from the Trentino as a Lab initiative of the European Network of the Living Labs at Trentino Digitale, the EU SEALS project, as well as the Pistoia Alliance Ontologies Mapping project and IBM Research.

TasLab logo        IT logo        IT logo        Pistoia Alliance logo        IBM Research logo       
Footer Hosted at DISI, UniTn :: Last Update: 22.12.2021 ::