Bridges are associated with extensive data throughout their lifecycle, particularly during design and operational phases. Existing bridge data is stored in various national and international databases. This data can consist of geometric parameters, structural details, environmental conditions and is often available in non-machine-readable varying file formats. These inconsistencies hinder performance evaluations and AI applications. Ontologies based on the Web Ontology Language (OWL) could offer a solution for harmonizing this data. This paper proposes an ontology-driven approach that integrates open-source data for advanced semantic querying, enhancing consistency and enabling the potential of informed decision-making in bridge design through a harmonized, machine-interpretable model.