Housing Potential Common Data Model and City Digital Twin
Megan Katsumi, Mark Fox, Anderson Wong, Divnoor Chatha

TL;DR
This paper presents the Housing Potential Common Data Model (HPCDM) to facilitate integrated housing analysis, along with a City Digital Twin and a pilot dashboard to demonstrate practical application.
Contribution
It introduces a standard data model for housing potential analysis and demonstrates its implementation through a digital twin and dashboard, addressing data silos.
Findings
HPCDM enables data integration across diverse datasets.
The City Digital Twin supports housing potential evaluation.
A pilot dashboard demonstrates practical usability.
Abstract
The evaluation of housing potential requires consideration of a location from multiple perspectives, ranging from zoning and land use to population characteristics and access to services. This research introduces the Housing Potential Common Data Model (HPCDM) to overcome existing data silos, serving as a standard to support integration and interoperability across the diverse range of datasets that are required for housing potential analysis. This report details the evaluation of the model along with the creation of a City Digital Twin for housing and a pilot dashboard application to demonstrate a practical implementation. Beyond the technical framework, this work identifies critical barriers to adoption and provides actionable mitigation strategies for urban planners and stakeholders.
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