Knowledge Representation and Reasoning with Domain Information System (DIS)

Abstract

Ontology engineering lacks a systematic, data-driven methodology, often requiring manual, ad hoc processes that struggle to integrate structured datasets with conceptual domain knowledge. Traditional approaches, particularly those based on Description Logic (DL), prioritise top-down taxonomic modelling, making it difficult to align with structured data sources that follow different relational paradigms. This disconnect leads to complex mapping efforts and possible semantic inconsistencies. To address these challenges, we propose a data-driven methodology grounded in the Domain Information System (DIS) formalism, and designed to align domain conceptualisation with existing structured datasets from the outset.