Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding

TL;DR

This paper introduces an ontology reshaping method that automates converting a domain ontology into a smaller, data-specific schema for knowledge graph generation, incorporating user preferences, demonstrated on industrial data.

Contribution

It proposes a novel ontology reshaping approach that balances knowledge and data orientation, with user-in-the-loop customization for industrial knowledge graph schemas.

Findings

Effective reshaping of ontologies demonstrated on real industrial data

Promising results in balancing general knowledge and data specifics

User preferences can be integrated into the ontology reshaping process

Abstract

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.