The pervasive deployment of “smart city” and “smart building” projects in cities world-wide is driving innovation on many fronts including; technology, telematics, engineering and entrepreneurship. This paper focuses on the technical and engineering perspectives of BIM and smart cities, by extending building and urban morphology studies as to respond to the challenges posed by Big Data, and smart infrastructure. The proposed framework incorporates theoretical and modelling descriptions to verify how network-based models can act as the backbone skeletal representation of both building and urban complexity, and yet relate to environmental performance and smart infrastructure. The paper provides some empirical basis to support data information models through building dependency networks as to represent the relationships between different existing and smart infrastructure components. These dependency networks are thought to inform decisions on how to represent building and urban data sets in response to different social and environmental performance requirements, feeding that into void and solid descriptions of data maturity models. It is concluded that network-based models are fundamental to comprehend and represent the complexity of cities and inform urban design and public policy practices, in the design and operation phases of infrastructure projects.