Workshops
The 17th International Workshop on Ontology Matching (OM)
Duration: Full Day
Organizers: Pavel Shvaiko, Jérôme Euzenat, Ernesto Jimenez-Ruiz, Oktie Hassanzadeh and Cassia Trojahn
Abstract: 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 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.
Webpage: http://om2022.ontologymatching.org
Wikidata Workshop
Duration: Half Day
Organizers: Lucie-Aimée Kaffee, Simon Razniewski, Kholoud Alghamdi and Gabriel Maia Rocha Amaral
Abstract: Wikidata is an open knowledge base hosted by the Wikimedia Foundation that can be read and edited by both humans and machines. Wikidata acts as the central source of common, open structured data used by Wikipedia, Wiktionary, Wikisource, and others. It is used in a variety of academic and industrial applications.
In recent years, we have seen an increase in the number of scientific publications around Wikidata. While there are a number of venues for the Wikidata community to exchange, none of those publish original research. We want to bridge the gap between these communities and the research events and give the research-focused part of the Wikidata community a venue to meet and exchange information and knowledge.
The Wikidata Workshop 2022 focuses on the challenges and opportunities of working on a collaborative open-domain knowledge graph such as Wikidata, which is edited by an international and multilingual community. We encourage submissions that observe the influence such a knowledge graph has on the web of data, as well as those working on improving this knowledge graph itself. This workshop brings together everyone working around Wikidata in both the scientific field and industry to discuss trends and topics around this collaborative knowledge graph.
Webpage: https://wikidataworkshop.github.io/2022/
International Workshop on Artificial Intelligence Technologies for Legal Documents (AI4LEGAL)
Duration: Half Day
Organizers: María Navas-Loro, Manolis Koubarakis, Ken Satoh and Sabrina Kirrane
Abstract: The legal domain applies to every aspect of people’s living and evolves continuously, building a huge network of interlinked legal documents. Therefore, it is important for a government to offer services that make legal information easily accessible to the citizens, enabling them to defend their rights, auditing public procurement, or to use legislation as part of their job. It is equally important to have professionals (lawyers, judges, administrations, etc.) access legislation in ways that allow them to do their job easily (e.g., they might need to be able to see the evolution of a law over time). Despite recent efforts to make all this accessible and transparent to both citizens and the companies involved, the level of implementation in different countries and layers of public administration still makes access difficult. For this reason, in the age of the Web it is important to develop applications for citizens and professionals easily, by connecting the available legal information with other kinds of government or private sector information.
The vision of the AI4LEGAL workshop is to bring together Artificial Intelligence and practitioners to discuss the digitization of legal documents, such as legislation and public procurement data, in today’s interconnected world.
Webpage: https://ai4legal.linkeddata.es
The 7th International Workshop on Visualization and Interaction for Ontologies and Linked Data (VOILA)
Duration: Half Day
Organizers: Bo Fu, Patrick Lambrix and Catia Pesquita
Abstract: A picture is worth a thousand words’, we often say, yet manyareas are in demand of sophisticated visualization techniques, and theSemantic Web is not an exception. The size and complexity of ontologies and Linked Data in the Semantic Web constantly grows and the diverse backgrounds of the users and application areas multiply at the same time. Providing users with visual representations and sophisticated
interaction techniques can significantly aid the exploration and under-standing of the domains and knowledge represented by ontologies and
Linked Data. There is no one-size-fits-all solution but different use cases demand different visualization and interaction techniques. Ultimately,
providing better user interfaces, visual representations and interaction techniques will foster user engagement and likely lead to higher quality
results in different applications employing ontologies and proliferate the consumption of Linked Data.
Webpage: http://voila2022.visualdataweb.org/
The 8th Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW)
Duration: Half Day
Organizers: Fabrizio Orlandi, Damien Graux, Emetis Niazmand and Maria Esther Vidal
Abstract: There is a vast and rapidly increasing quantity of scientific, corporate, government, and crowd-sourced data openly published on the Web. Open Data plays a catalyst role in the way structured information is exploited on a large scale. A traditional view of digitally preserving these datasets by “pickling and locking them away” for future use, like groceries, conflicts with their evolution. There are several approaches and frameworks (Linked Data Stack, PoolParty Suite, etc.) that manage a full life-cycle of the Data Web. More specifically, these solutions are expected to tackle major issues such as the synchronisation problem (monitoring changes), the curation problem (repairing data imperfections), the appraisal problem (assessing the quality of a dataset), the citation problem (how to cite a particular version of a dataset), the archiving problem (retrieving a specific version of a dataset), and the sustainability problem (preserving at scale, ensuring long-term access). During the past seven years, the MEPDaW workshop series has been gathering researchers from the community around these challenges. So far the series successfully published more than 50 research efforts allowing more than 60 individual authors to present and share their ideas.
Webpage: https://mepdaw-ws.github.io/2022
Workshop on Deep Learning for Knowledge Graphs (DL4KG)
Duration: Full Day
Organizers: Mehwish Alam, Davide Buscaldi, Michael Cochez, Francesco Osborne, Diego Reforgiato Recupero and Harald Sack
Abstract: Over the past years there has been a rapid growth in the use and the importance of Knowledge Graphs (KGs) along with their application to many important tasks. KGs are large networks of real-world entities described in terms of their semantic types and their relationships to each other. On the other hand, Deep Learning methods have also become an important area of research, achieving some important breakthrough in various research fields, especially Natural Language Processing (NLP) and Image Recognition.
In order to pursue more advanced methodologies, it has become critical that the communities related to Deep Learning, Knowledge Graphs, and NLP join their forces in order to develop more effective algorithms and applications. This workshop, in the wake of other similar efforts at previous Semantic Web conferences such as ESWC2018 as DL4KGs and ISWC2018, ESWC2019, ESWC 2020, ISWC2021 aims to reinforce the relationships between these communities and foster inter-disciplinary research in the areas of KG, Deep Learning, and Natural Language Processing.
Webpage: https://alammehwish.github.io/dl4kg2022/
The 13th Workshop on Ontology Design and Patterns (WOP)
Duration: Full Day
Organizers: Vojtěch Svátek, Valentina Anita Carriero, María Poveda-Villalón, Christian Kindermann and Lu Zhou
Abstract: The 13th edition of the Workshop on Ontology Design and Patterns (WOP) will cover issues related to quality in ontology design and ontology design patterns (ODPs) for data and knowledge engineering in Semantic Web. The increased attention to ODPs in recent years through their interaction with emerging trends of Semantic Web such as knowledge graphs can be attributed to their benefit for knowledge engineers and Semantic Web developers. Such benefits come in the form of direct links to requirements, reuse, guidance, and better communication. The workshop’s aim is thus not just: 1) providing an arena for discussing patterns, pattern-based ontologies, systems, datasets, but also 2) broadening the pattern community by developing its own “discourse” for discussing and describing relevant problems and their solutions. A recent development in the Semantic Web community is that the general idea of “pattern” has begun to appear in different but related forms, and at WOP 2022, we intend to continue to include these new trends. We plan a full-day workshop consisting of three parts: a keynote, presentations of contributed papers, and a community session discussing joint long-term initiatives, with break-out sessions addressing specific problems.
Webpage: http://ontologydesignpatterns.org/wiki/WOP:2022
International Workshop on Knowledge Graph Summarization (KGSum)
Duration: Half Day
Organizers: Carlos Badenes-Olmedo, Jose Luís Redondo-García, Nandana Mihindukulasooriya and Maribel Acosta
Abstract: There is a growing interest in generating summaries from the facts contained in a Knowledge Graph. Condensing relevant information into a few statistic data, sentences, paragraphs, or triplets is an emerging problem that remains to be solved as knowledge graphs increase complexity and expand in size and domains. Knowledge Graph Summarization (KGSum) aims at producing concise but informative descriptions of the content of a knowledge graph that help users to efficiently access and distill valuable information from it. Conversational systems, question-answering services or any other method leveraging the narrative content around the entities in a knowledge graph will benefit from these techniques.
Webpage: https://kgsum.github.io
The 6th Workshop on Storing, Querying and Benchmarking Knowledge Graphs (QuWeDa)
Duration: Half Day
Organizers: Muhammad Saleem and Axel-Cyrille Ngonga Ngomo
Abstract: The constant growth of Knowledge Graphs (KGs) on the Web raises new challenges for querying and integrating massive amounts of data across multiple KGs. Such KGs are available through various interfaces, such as data dumps, Linked Data Platform, SPARQL endpoints and Triple Pattern Fragments. In addition, various sources produce streaming data. Efficiently querying these sources is of central importance for the scalability of Linked Data and Semantic Web technologies. To exploit the massive amount of data to its full potential, users should be able to query and combine this data easily and effectively. This workshop at the International Semantic Web Conference (ISWC) seeks original articles describing theoretical and practical methods and techniques for fostering, querying, consuming, and benchmarking KGs.
Webpage: https://sites.google.com/view/quweda2022
Musical Heritage Knowledge Graphs
Duration: Half Day
Organizers: Valentina Presutti, Michel Buffa, Luc Steels, Jean-François Trubert, Enrico Daga and Albert Meroño Peñuela
Abstract: Music is a key component of our cultural heritage as well as a driver for the creative industry. As such it is studied from a social science and humanities perspective as well as from a computer science one.
Recently, knowledge graphs have shown the potential to become an enabling technology for the hybridisation and collaboration between these two research worlds. They can be used for feeding AI applications to support musicologists, musicians, producers, etc. in tasks such as music management, analysis, composition, and generation. And they are key for developing a new generation of music information retrieval applications, based on interlinked knowledge as opposed to isolated collections.
This workshop intends to bring together an interdisciplinary audience of researchers and practitioners, including digital artists, to present their most recent use cases and results on methods, tools and applications for building, analyzing, exploiting, and interacting with musical heritage knowledge graphs.
Webpage: https://mhkg-workshop.i3s.univ-cotedazur.fr/