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. © 2014 IFIP International Federation for Information Processing.
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CITATION STYLE
Ghiassi, N., Glawischnig, S., Pont, U., & Mahdavi, A. (2014). Toward a data-driven performance-guided urban decision-support environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8407 LNCS, pp. 96–107). Springer Verlag. https://doi.org/10.1007/978-3-642-55032-4_10
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