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During the design and engineering phase of a new building, computer-based simulations are commonly used to understand, analyze, and predict the performance of the new building such as energy, water, thermal comfort, indoor air quality, lighting, and acoustics. Often, such simulations require two indispensable ingredients in order to produce reliable and accurate simulations: i) a significant amount of empirical data for modeling, calibration, and validation; and, ii) insightful knowledge of anticipated humanbuilding interactions for the building under design. Empirical data are conventional sources for creating simulation models. However, since each building is unique, simulations based solely on empirical data are often not able to address fully the unique context of a new building. In addition, even though contemporary technologies enable researchers, designers, and engineers to collect large amounts of data for various types of buildings, access to such data across organization and ownership boundaries often is challenging due to concerns such as interoperability, shareability, data size, transport costs, and privacy. Therefore, the identification of effective methods to combine these two ingredients (distributed raw data and understanding human-building interactions during design) for building performance simulations remains an open challenge within the building design and engineering communities. Recent advances in computing technologies and data analysis methods offer new opportunities to improve computer-based, new building simulations that otherwise remain underexplored by the broader research community. For example, we are conducting new building simulation experiments within an open computing infrastructure based on the concept of dynamic data-driven application systems (DDDAS). This infrastructure, called the Virtual Information Fabric Infrastructure (VIFI) [1], combines cyberinfrastructure data, data science methods, and immersive computing capabilities in a manner that presents a new approach for conducting building performance simulations. The VIFI approach is complementary to the conventional data-centric sharing strategy, which focuses on transporting raw data for subsequent analyses. Instead, the

Application of the Virtual Information Fabric Infrastructure (VIFI) to Building Performance Simulations