Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding
This work addresses the problem of automating knowledge graph generation for industrial applications like Bosch welding, but it appears incremental as it builds on existing ontology engineering approaches.
The paper tackles the challenge of balancing knowledge-oriented and data-oriented principles in ontology design for knowledge graph generation by introducing an ontology reshaping method that automates conversion to a smaller KG schema, demonstrating promising results on real industrial welding data.
Knowledge graphs (KG) are used in a wide range of applications. The automation of KG generation is very desired due to the data volume and variety in industries. One important approach of KG generation is to map the raw data to a given KG schema, namely a domain ontology, and construct the entities and properties according to the ontology. However, the automatic generation of such ontology is demanding and existing solutions are often not satisfactory. An important challenge is a trade-off between two principles of ontology engineering: knowledge-orientation and data-orientation. The former one prescribes that an ontology should model the general knowledge of a domain, while the latter one emphasises on reflecting the data specificities to ensure good usability. We address this challenge by our method of ontology reshaping, which automates the process of converting a given domain ontology to a smaller ontology that serves as the KG schema. The domain ontology can be designed to be knowledge-oriented and the KG schema covers the data specificities. In addition, our approach allows the option of including user preferences in the loop. We demonstrate our on-going research on ontology reshaping and present an evaluation using real industrial data, with promising results.