Abstract
Data are continuously generated during the lifetime of the building, and mainly stored in Building Information Models (BIMs) and Building Automation Systems (BASs). BIMs store the static and spatial design and construction data, while BASs store the dynamic/temporal operational data. The data from these two e-resources are highly complementary. Effective data integration can provide a more complete spatiotemporal description of a building and bridge information gaps among different stages of a building life cycle. The data integration also facilitates the transition of the AEC industry in the pervasive big data revolution. This chapter first reviews BIM and BAS data exchanges and integration schemas and their applications in building energy management. Then, the challenges in analyzing big building data are identified. After that, a big data analysis framework incorporating machine learning for utilizing big building data is proposed and demonstrated. Finally, this chapter is concluded with remarks on prospects and challenges.
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