COntExt: Towards Context-Aware Ontology Extension from Operational Metrics

Organizations track vast operational metrics, but connecting these structured metric catalogues to formal ontologies is typically manual and labor-intensive, leaving valuable domain knowledge disconnected. COntExt automates this by using metric definitions and their context to suggest how new concepts should be integrated into existing ontologies, breaking the task into parent-class prediction, relation-type prediction, and data-property assignment. Tested across four cybersecurity ontologies, it outperforms context-free baselines. This is useful for organizations maintaining knowledge graphs or ontologies in domains like cybersecurity, compliance, or systems monitoring, significantly reducing the cost of ontology upkeep. Authors: Hussain Hussain, Stefan Schöberl, Angelika Schneider, Verena Paper: https://arxiv.org/abs/2607.29553v1