Abstract. This volume encompasses the proceedings of SEMANTiCS 2023, the 19th International Conference on Semantic Systems, a pivotal event for professionals and researchers actively engaged in harnessing the power of semantic computing. At SEMANTiCS, attendees gain a profound understanding of its transformative potential, while also confronting the practical limitations it presents. Each year, the conference magnetizes information managers, IT architects, software engineers, and researchers from a broad spectrum of organizations, spanning research facilities, non-profit entities, public administrations, and the world’s largest corporations.
Keywords. Semantic Systems, Knowledge Graphs, Artificial Intelligence, Semantic Web, Linked Data, Machine Learning, Knowledge Discovery
SEMANTiCS serves as a vibrant platform facilitating the exchange of cutting-edge scientific findings in the realm of semantic systems. Furthermore, it extends its scope to encompass novel research challenges in areas such as data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web. Having reached its 19th year, the conference has evolved into a distinguished international event that seamlessly bridges the gap between academia and industry.
Participants and contributors of SEMANTiCS gain invaluable insights from esteemed researchers and industry experts, enabling them to stay abreast of emerging trends and themes within the vast field of semantic computing. The SEMANTiCS community thrives on its diverse composition, attracting professionals with multifaceted roles encompassing artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management.
In 2023, the conference embraced the subtitle “Towards Decentralized Knowledge Eco-Systems” and particularly welcomed submissions pertaining to the following topics:
∙ Web Semantics & Linked (Open) Data
∙ Enterprise Knowledge Graphs, Graph Data Management
∙ Machine Learning Techniques for/using Knowledge Graphs (e.g. reinforcement learning, deep learning, data mining and knowledge discovery)
∙ Knowledge Management (e.g. acquisition, capture, extraction, authoring, integration, publication)
∙ Terminology, Thesaurus & Ontology Management
∙ Reasoning, Rules, and Policies
∙ Natural Language Processing for/using Knowledge Graphs (e.g. entity linking and resolution using target knowledge such as Wikidata and DBpedia, foundation models)
∙ Crowdsourcing for/using Knowledge Graphs
∙ Data Quality Management and Assurance
∙ Mathematical Foundation of Knowledge-aware AI
∙ Multimodal Knowledge Graphs
∙ Semantics in Data Science
∙ Semantics in Blockchain environments
∙ Trust, Data Privacy, and Security with Semantic Technologies
∙ Economics of Data, Data Services, and Data Ecosystems
∙ IoT and Stream Processing
∙ Conversational AI and Dialogue Systems
∙ Provenance and Data Change Tracking
∙ Semantic Interoperability (via mapping, crosswalks, standards, etc.)
∙ Digital Humanities and Cultural Heritage
∙ LegalTech, AI Safety, Explainable and Interoperable AI
∙ Decentralized and/or Federated Knowledge Graphs
Application of Semantically Enriched and AI-Based Approaches:
∙ Knowledge Graphs in Bioinformatics and Medical AI
∙ Clinical Use Case of AI-based Approaches
∙ AI for Environmental Challenges
∙ Semantics in Scholarly Communication and Open Research Knowledge Graphs
∙ AI and LOD within GLAM (galleries, libraries, archives, and museums) institutions
The Research and Innovation track garnered significant attention with 54 submissions after a call for papers was publicly announced. To ensure meticulous evaluations, an esteemed program committee comprising 85 members collaborated to identify the papers of utmost impact and scientific merit. Implementing a double-blind review process, wherein author identities and the reviewers were obscured to assure anonymity. A minimum of three independent reviews were conducted for each submission. Upon completion of all reviews, the program committee chairs meticulously compared and deliberated on the evaluations, addressing any disparities or differing viewpoints with the reviewers. This comprehensive approach facilitated a meta-review, enabling the committee to recommend acceptance or rejection of each paper. Ultimately, we were pleased to accept 16 papers, resulting in an acceptance rate of 29.6%.
In addition to the peer-reviewed work, the conference had three renowned keynotes from Xin Luna Dong (Meta Reality Lab), Marco Varone (Expert.ai), and Aidan Hogan (Department of Computer Science, University of Chile).
Additionally, the program had posters and demos, a comprehensive set of workshops, as well as talks from industry leaders.
We thank all authors who submitted papers. We particularly thank the program committee which provided careful reviews in a quick turnaround time. Their service is essential for the quality of the conference.
Special thanks also go to our sponsors without whom this event would not be possible:
Gold Sponsors: Metaphacts, Pantopix, PoolParty, TopQuadrant
Silver Sponsors: GNOSS, IOLAR, Ontotext, neo4j, RDFOX, The QA Company
Bronze Sponsor: RWS
Startup Sponsor: Karakun, SP Semantic Partners
Leipzig, September 2023