The vision of the Semantic Web is to enhance today's web via the exploitation of machine-processable meta data. The explicit representation of the semantics of data, accompanied with domain theories (ontologies), will enable a web that provides a qualitatively new level of service. It will weave together an incredibly large network of human knowledge and will complement it with machine processability. Various automated services will help the user achieve goals by accessing and providing information in machine-understandable form. This process may ultimately create extremely knowledgeable systems with various specialized reasoning services systems. Many technologies and methodologies are being developed within Artificial Intelligence, Human Language Technology, Machine Learning, Databases, Software Engineering and Information Systems that can contribute towards the realization of this vision.

• Languages, Tools and Methodologies for Semantic Annotation of Web Data
• (Semi-)automatic ontology learning and metadata generation (Including HLT and machine learning approaches)
• Ontology Management (creation, merging, linking, mediation and reconciliation)
• Semantic Web Services (service description, discovery, invocation, composition)
• Semantic Web-based Knowledge Management
• Data Semantics
• Database Technologies for the Semantic Web
• Semantic Knowledge Portals
• Semantic Brokering
• Semantic Interoperability
• Semantic Web Mining
• Semantic Web Inference Schemes
• Semantic Web Trust, Privacy, Security and Intellectual Property Rights
• Semantic Web for e-Business and e-Learning
• Semantic Searching and Querying
• Visualization and modelling