The 18th International Workshop on
November 6th or 7th, 2023,
International Semantic Web Conference (ISWC) Workshop Program,
M.A.I.C.C., Athens, Greece
BRIEF DESCRIPTION AND OBJECTIVES
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
These correspondences can be used for various tasks, such as ontology
merging, data interlinking, query answering or navigation over knowledge
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, knowledge graph and web table 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) 2023 campaign:
To examine similarities and differences from other, old, new and emerging,
techniques and usages, such as web table matching or knowledge embeddings.
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;
Formal foundations and frameworks for matching;
Novel matching methods, including link prediction, ontology-based
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;
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;
Reasoning with alignments;
Alignment coherence and debugging;
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
as well as participating in the OAEI 2023 campaign. Long technical papers
be of max. 12 pages. Short technical papers should be of max. 6 pages.
Posters/statements of interest should not exceed 3 pages.
All contributions have to be prepared using the CEUR-ART, 1-column style.
Overleaf page for LaTeX users is available at
while offline version with the style files is available from
Submissions should be uploaded in PDF format
through the workshop submission site at:
Contributors to the OAEI 2023 campaign have to follow the campaign
and schedule at http://oaei.ontologymatching.org/2023/
DATES FOR TECHNICAL PAPERS AND POSTERS:
July 31st, 2023: Deadline for the submission of papers.
August 28th, 2023: Deadline for the notification of
September 4th, 2023: Workshop camera ready copy submission.
November 6th or 7th, 2023: OM-2023, M.A.I.C.C., Athens, Greece.
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.
1. Pavel Shvaiko (main contact)
Trentino Digitale, Italy
2. Jérôme Euzenat
INRIA & Univ. Grenoble Alpes, France
3. Ernesto Jiménez-Ruiz
City, University of London, UK & SIRIUS, University of Oslo, Norway
4. Oktie Hassanzadeh
IBM Research, USA
5. Cássia Trojahn
Alsayed Algergawy, Jena University, Germany
Manuel Atencia, Universidad de Málaga, Spain
Jiaoyan Chen, University of Oxford, UK
Jérôme David, University Grenoble Alpes & INRIA, France
Gayo Diallo, University of Bordeaux, France
Daniel Faria, INESC-ID&IST, University of Lisbon, 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, University of Edinburgh, UK
Hoa Ngo, CSIRO, Australia
George Papadakis, University of Athens, Greece
Catia Pesquita, University of Lisbon, Portugal
Henry Rosales-Méndez, University of Chile, Chile
Booma Sowkarthiga, Microsoft, USA
Kavitha Srinivas, IBM, USA
Giorgos Stoilos, University of Oxford, UK
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
Lu Zhou, TigerGraph, USA
More about ontology matching:
Pavel Shvaiko, PhD
Trentino Digitale, Italy
Cap. Soc. Euro 6.433.680,00 - REG. IMP. / C.F. / P.IVA 00990320228
tndigit(a)tndigit.it <mailto:email@example.com> - www.trentinodigitale.it
Società soggetta ad attività di direzione
e coordinamento da parte della Provincia Autonoma di Trento - C.Fisc.
Questo messaggio è indirizzato esclusivamente ai destinatari
in intestazione, può contenere informazioni protette e riservate ai sensi
della normativa vigente e ne è vietato qualsiasi impiego diverso da quello
per cui è stato inviato. Se lo avete ricevuto per errore siete pregati di
eliminarlo in ogni sua parte e di avvisare il mittente