Toward a Data-Driven Performance-Guided Urban Decision-Support Environment
Abstract
The present contribution briefly represents the structure and main features of SEMERGY, a performance-guided multi-objective building optimization environment, supported by Semantic Web technologies. It establishes the importance of urban-scale performance considerations, discusses particular features of urban data, and suggests a framework to upscale the SEMERGY approach towards development of a data-driven performance-guided urban decision support environment. The suggested task-based ontology framework can facilitate data and knowledge sharing within the domain of urban performance inquiries.
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