Despite its potential, incorporating ontologies into database conceptual modelling poses challenges related to semantic heterogeneity, the complexity of ontology engineering, and methodological rigour. This call for papers invites contributions that advance theoretical, methodological, and practical aspects of ontology-driven conceptual modelling for databases, with the aim of fostering more interoperable, intelligent, and semantically grounded data infrastructures.
Ontology-driven conceptual modelling addresses limitations of traditional database models, such as the relational and Entity–Relationship paradigms, by introducing shared vocabularies and formally defined concepts aligned with domain knowledge. This alignment is particularly relevant in domains where semantic accuracy is critical, such as healthcare, finance, and intelligent, data-driven systems. At the same time, it reflects a methodological shift from schema-centric to knowledge-centric data management, supporting advanced capabilities such as semantic querying, reasoning, and integration with knowledge graphs.
Although it has potential, incorporating ontologies into database conceptual modelling poses challenges related to semantic heterogeneity, the complexity of ontology engineering, and methodological rigour. This call for papers invites contributions that advance theoretical, methodological, and practical aspects of ontology-driven conceptual modelling for databases, with the aim of fostering more interoperable, intelligent, and semantically grounded data infrastructures.
