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 the Semantic Web 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 (including 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, semantic analysis, and Large Language Models
    Integration of the Semantic Web with:
        Machine learning, data mining, and neural symbolic reasoning
        Generative AI (Large Language Models)
        User interfaces, usability, and accessibility
        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)
    Semantic Web Agents including:
        Autonomous systems, including multi-agent systems and robotics
        Architecture characteristics for autonomy exploiting KGs
        Incomplete or conflicting knowledge, beliefs, and assumptions and KGs
        Human-machine social interactions and KGs
        Architecture characteristics for exploiting KGs autonomously
        Development platforms and frameworks for exploiting KGs in an autonomous manner
        Governance of autonomous agents on the Web

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.