Zoning regulations in the Greater Toronto Area (GTA) are governed by a decentralized system in which 25 municipalities independently define land use permissions, development standards, and zoning classifications. Although operating under a shared provincial framework, these municipalities employ inconsistent zoning terminologies and abbreviation systems, resulting in significant semantic fragmentation. This lack of standardization introduces inefficiencies in development approvals, increases reliance on manual interpretation, and limits the effectiveness of digital planning tools such as GIS and automated compliance systems. This study introduces Zonology, an ontology-based framework designed to harmonize zoning semantics across multi-jurisdictional planning systems while preserving municipal autonomy. Developed using the Linked Open Terms (LOT) methodology and implemented in OWL, the framework establishes formal relationships between zoning designations, permitted land uses, and development standards. A proof-of-concept case study aligning the City of Toronto and the City of Markham demonstrates the ability to integrate over 60 zoning categories and 150 land uses within a unified semantic structure. Results show high precision and recall in competency question queries, confirming the model’s effectiveness in enabling cross-jurisdictional interpretation. Zonology provides a scalable foundation for interoperable urban planning, supporting digital permitting, data-driven decision-making, and Artificial Intelligence (AI) assisted governance.