KG Engineering and Information Retrieval develops methods and tools to construct, integrate, enrich, and query knowledge graphs that connect heterogeneous industrial information. Building on the semantic foundation provided by domain ontologies, this area investigates data mapping, interoperability between graph representations, entity linking, and retrieval strategies that combine textual, vector, and graph-based information. Its research also explores natural-language-to-SPARQL translation, RAG and GraphRAG, context selection, and the evaluation of whether retrieved evidence is sufficient to support an answer. Within OntoKG, this area connects structured knowledge to users’ information needs, helping them navigate relationships among equipment, processes, and operational records. By investigating retrieval quality and the factual support of generated answers, it aims to make technical information easier to access and more useful for analyzing incidents that may affect production capacity.