Analytics for Building-Scale Sustainable Ecosystems

ISBN Print: 978-1-56700-279-9

ISBN Online: 978-1-56700-288-1

DOI: 10.1615/978-1-56700-279-9.0

Yongxin Tao(open in a new tab) Department of Mechanical Engineering, Cleveland State University, 2121 Euclid Ave, Cleveland, OH 44114, USA
Yi Jiang(open in a new tab) Department of Building Science, Tsinghua University, Beijing 100084, China

Chapter 6: System Integration for Interoperable Data Models of Building-Scale Ecosystem

DOI: 10.1615/978-1-56700-279-9.190

The building delivery process is commonly executed as a discrete and sequential set of activities. This industry phenomenon is the result of a historical evolution driven by many factors. As building design becomes ever increasingly complex due to changing demands of developers in a competitive globalized real estate market, specialist professional communities have emerged, bringing specific knowledge to the building delivery process beyond the capabilities of the conventional architectural and building engineering professions. Although this might seem a rational step toward addressing the complexity involved, it also inevitably and fundamentally transforms the originally integrated process to one of fragmentation and compartmentalization. This in turn necessitates the development of communication frameworks based on the organization of activities for the purpose of establishing a professional fee structure that is commensurate with the scope of work and level of responsibility at various project phases. The quest for more efficient communication methods has gradually evolved into a circulus vitiosus, whereby advances in communication and dissemination technologies continuously struggle to cope with an unprecedented rate of information growth globally, while continuing (if not intensifying) the trend toward process disintegration. Superficial attempts to patch the current decision-making approaches often lead to miscommunication of intentions resulting in unsatisfactory solutions that are costly to remedy in terms of time and resources. While the capabilities of various decision support tools are nonetheless expanding, they still fall short of anticipating or challenging the very logic of the industry processes they are supposed to support.

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