We encourage papers that directly contribute to the advancement of the Semantic Web area. The relationship to the core area of the conference needs to be clearly described in the submitted work. Submissions beyond the scope will be desk-rejected. Topics in this area include, but are not limited to: Ontologies and Capturing Knowledge including: Ontology engineering and ontology patterns Ontology modularity, mapping, merging, and alignment Information extraction, knowledge graph construction Representation, management, and applications of Knowledge Graphs (incl. RDF and property graphs), including: Knowledge Representation and Reasoning Search, query, integration, and analysis Robust and scalable management Information visualization and exploratory analysis Databases and ontology-based data access, integration and exchange on the Web Knowledge graph centered natural language processing, information retrieval and semantic analysis, and large language models Integration of the Semantic Web with: Machine learning, data mining, and neural symbolic reasoning User interfaces, usability, and accessibility Autonomous systems, including multi-agent systems and robotics Data integration, quality assurance, and data provenance Social issues including trust, bias, fairness, privacy, security and policy Web services, process management, social Web, and Internet of Things Dynamic and streaming data, including complex event processing and stream reasoning Software engineering, algorithms, and decentralized architectures Specialized domains (geographical, biomedical, e-Science, multimedia, performing arts, public administration, cultural heritage, law, etc.) Artificial intelligence and hybrid approaches (including human-machine intelligence) We welcome descriptions of contributions that leverage knowledge representation based on Semantic Web standards or other graph data models to improve the acquisition, processing, and sharing of data on the Web. We require authors to explicitly highlight how their work could be applied in a Semantic Web setting.