ENHANCING THE URBAN DESIGN PROCESS FROM A DATA FAMILIARITY PERSPECTIVE

Abstract

With technological advances leading to new urban practices and contemporary problems, urban designers face significantly increasing pressure to process cross-disciplinary and transdisciplinary data for decision-making during the urban design process. From the design perspective, the data could be segmented into two groups: familiar and unfamiliar. Currently how to explore/exploit the unfamiliar data remains a big challenge for designers during the design process. Hence, this research identifies major research questions that may be possible to investigate with the unfamiliar data and identifies three themes for the use of data familiarity perspective in improving/optimizing the urban design process: a) accuracy, b) prediction and c) guidance. The results of three case studies prove the proposed data method could inform and guide the designer pursuing energy performance during the urban design process. The data familiarity perspective method will play a vital role for decision-making for urban design in the future.