The most recent conference I participated in was SEMANTiCS, September 20-22, in Leipzig Germany. This was the 19th year of this European conference focused on the application of semantic technologies and systems. This was also my fourth year presenting a workshop/tutorial on taxonomies and ontologies at the conference. The widespread value of taxonomies across different areas of specialization is indicated by the fact that taxonomy workshops are repeatedly a part of conferences on various subjects, including semantics, knowledge management, library and information science, information architecture, content strategy, and digital asset management.
Semantics and taxonomies
Semantics means “meaning,” so semantic systems utilize standards to support the encoding of meaning of things/resources and their relations, making the semantics machine-readable. Various standards, guidelines, and data models for semantic systems were developed for what is called the Semantic Web. The Semantic Web goes beyond the simple hyperlinks of the World Wide Web to label shared metadata, specify the kinds of relations. This supports linked data, and the linking of taxonomies to other taxonomies and ontologies and their tagged content or data, which are stored on different servers.
Just as World Wide Web protocols have been adapted within enterprises (“behind the firewall”), so have Semantic Web standards. You don’t have to share your data publicly to reap the benefits of the Semantic Web: open standards to enable the migration of taxonomies and related data between systems, sharing of data with partners, extracting and transforming data from within silos across the enterprise into a standard format, and the ability to link to data on the Web to bring in new content even if not sharing content out on the Web.
Taxonomies, as controlled vocabularies, have always been about concepts, each with unique understood meaning, not just words or strings of text. So, using taxonomies is using semantics. The Semantic Web standard SKOS (Simple Knowledge Organization System) specifies a data model to make taxonomies and other knowledge organization systems (thesauri, classification systems, etc.) machine-readable and interchangeable on the Web. Semantic Web standards also cover ontologies with RDF-Schema and OWL. By following Semantic Web Standards, taxonomies can easily be linked to and extended with ontologies, and then by linking to data stored in a graph database, knowledge graphs can be built.
The SEMANTiCS conference
The SEMANTiCS conference is somewhat unique by being semi-academic and semi-industry. It has separate academic track and industry track chairs and additional tutorials and workshops. It’s good to bring academia and industry together in a field like this, where research topics can be applied and partnerships can be developed. The location of the conference varies, and it partners with a local higher education institution for logistical support, with graduate students volunteering to help in exchange to getting access to sessions.
This was the second year that SEMANTiCS combined its conferences with the Language Technology Industry Association, which organized a Language Intelligence track, dealing with technologies for the management of terminology, multilingual content, and machine translation. The conference also includes a one-day track focused on DBpedia, which is not the same first day as the tutorials and workshops. The entire conference lasts three full days, and has a social event one evening, and a dinner on the second evening.
The conference has industry vendor sponsors, about eight of which were exhibiting, and a few more which did not exhibit. There are also slightly more organizations which are “partners,” including DBpedia, The Alan Turing Institute, and a number of institutes of higher education in Europe which have programs in semantic technologies. Additional organizers include Semantic Web Company, Institut für Angewandte Informatik and the Vjije Universities Amsterdam, representing the three countries where SEMANTiCS has been taking place: Austria, Germany, and Netherlands.
The 2023 conference was held September 20-22 in Leipzig, Germany, under the leadership of a new chair Sahar Vahdati of Technical University Dresden. There were about 285 participants in person and about one-third as many online. The conference has been hybrid since 2021. There were often six simultaneous sessions. Themed tracks or sessions of multiple speakers included Knowledge Graphs, Reasoning & Recommendation, Natural Language Processing and Large Language Models, Legal & Data Governance, Ontologies Data Management, and Environmental-Social-Governance (ESG). While there was not a life sciences track like last year, there was a themed subject track on cultural heritage. LLMs and ESG were both new topics this year. Poster presentations also covered the range of topics.
Knowledge graphs is a regular theme at this conference, but this time there was the addition of LLMs. The opening keynote was “Generations of Knowledge Graphs: The Crazy Ideas and the Business” presented by Xin Luna Dong of Meta. She spoke of three generations of knowledge graphs: entity-based knowledge graphs, text-rich knowledge graphs, and dual neural knowledge graphs, using an ontology and LLMs. The second day’s keynote was “Knowledge Graphs in the Age of Large Language Models,” presented by Aiden Hogan of the University of Chile. LLMs and AI topics were also presented in the Knowledge Graphs track, such as in Andreas Blumauer’s talk “Responsible AI and LLMs.” Finally, the moderated closing panel was “Large Language Models and Knowledge Graphs: Status Quo - Risks - Opportunities” with panelists, Andreas Blumauer and Jochen Hummel from software vendors and Kristina Podnar, a digital policy consultant, who were not completely in agreement.
In addition to my 3-hour tutorial, “Knowledge Engineering of Taxonomies and Ontologies,” only slightly updated from last year, I also contributed, along with Lutz Krüger, to Andreas Blumauer’s new 3-hour tutorial “They Key to Sustainable Enterprises: ESG, KNowledge Graphs, and Digitalization.” Adopting an ESG program and complying with upcoming ESG directives requires connecting a lot of information and data and aligning it with requirements and disclosure categories, and this is where a knowledge graph can be extremely helpful. Other tutorials and workshops dealt with data spaces, ontology reasoning, healthcare NLP, NLP for knowledge graph construction, and FAIR ontologies.
Past and future
Semantic technologies were very new when the conference was first launched in 2005 by Semantic Web Company, even before launching its product PoolParty Semantic Suite. But it’s never been a vendor product-based conference. The main purpose was and still is to promote the understanding and advancement of semantic technologies. Competitor software vendors sponsor and exhibit, and Semantic Web Company has stepped back from a lead organizational role. The conference is not one where sponsors make business in selling their products or services, but rather for raising awareness, making and reinforcing partnerships, exchanging ideas, and general networking, including looking for work. It is more of a community conference than anything else, but it is an open welcoming community, with new people coming every year.