1st Workshop on AI-assisted Approaches to Knowledge Engineering (AIAA4KE)
co-located with ISWC 2026, 25-26 October 2026, Bari, Italy
co-located with ISWC 2026, 25-26 October 2026, Bari, Italy
The AI Assistants for Knowledge Engineering (AIAA4KE) 2026 workshop explores the potential of generative AI and agentic workflows in Knowledge Engineering. While AI-assisted approaches have revolutionised general software engineering, and ontologies and knowledge graphs (KGs) have been recognised as valuable components of AI systems, knowledge engineering -- including ontology modelling and knowledge graph construction -- remains a bottleneck, reliant on scarce human expertise.
AIAA4KE should provide a platform to discuss topics such as multi-modal user intent analysis, automated ontology matching, and KG curation from diverse data sources. Key focus areas also include developing evaluation benchmarks, integrating emerging standards for AI-assisted approaches, such as MCP-based agentic systems, and implementing human-in-the-loop governance patterns for auditing AI-driven changes. We welcome presentations across the RDF/OWL and labelled property graph communities and seek to scale the application of knowledge engineering technologies through robust, industry-ready AI assistants.
With AIAA4KE, our aim is to connect the scientific, industrial, and standardisation communities by providing a platform for interaction between these communities with the following benefits:
For research communities at the intersection of AI assistants (that use generative AI) and Semantic Web technologies, the main focus is on developing methods and approaches with technical depth and soundness. However, they often miss the opportunity to show and test their work in real-world settings that practitioners can provide.
The community of industry practitioners is already building AI assistants for ontology and KG creation in various use cases. However, they face the challenge that Semantic Web technologies are not always easily accessible to practitioners without expert-level know-how, and the quality of generated ontologies and knowledge graphs, including their alignment, is often hard to evaluate.
The community of standardisation experts, who are active in both academia and industry and should bridge the gap between them, is often not given enough attention and should be more involved in our work.
Call for Papers is available now!