OntoKG is a research project that combines domain ontologies, knowledge graphs, and artificial intelligence to support production optimization and the effective use of productive capacity in the Oil and Gas (O&G) industry. Through shared definitions of entities, properties, and relationships, the project seeks to connect and contextualize information from corporate databases, and technical documents, including piping and instrumentation diagrams (P&IDs). Its research explores automated knowledge extraction, graph enrichment, and semantic information retrieval to enhance large language model applications, including RAG and GraphRAG. By enabling faster access to relevant information and answers grounded in traceable evidence, OntoKG aims to accelerate the identification and analysis of incidents that may affect productive capacity, supporting informed decisions and more efficient operations.

Project Areas

Domain Ontology Engineering

Develop and evolve domain ontologies to represent industrial knowledge and enable semantic interoperability.

KG Engineering and Information Retrieval

Build and integrate knowledge graphs to support semantic retrieval, natural-language queries, and question answering.

P&ID Knowledge Extraction and Graph Enrichment

Extract equipment, properties, and relationships from P&IDs to populate and enrich knowledge graphs.

Requirements Engineering

Identify use cases and define requirements aligned with industrial needs and project objectives.

Computational Infrastructure and Services

Provide computing infrastructure and shared services to support development, integration, and experimentation.

Academic Institutions

Partners and Funders