A new approach in data visualization to integrate time and space variability of daylighting in the design process

Abstract

Daylighting design has great impact on the performance and aesthetical quality of a work of architecture but requires many issues to be addressed during the design process. The way existing daylighting tools deliver data to designers is still inefficient. The output display has no quick switch between quantitative and qualitative data and simply considers single moments with fixed weather condition. Designers are interrupted in their design process, and they usually need to make a data synthesis themselves, with the risk of overlooking critical periods or aspects of the design. Therefore, this thesis proposed a new data visualization method to improve this situation and create a more efficient data transmission between the designer and the program to better inform and support the design process. It used some existing research work in progress and developed a functional data visualization platform to simultaneously present sufficient quantitative and qualitative data over the year while linking closely the performance to annual weather variations, sun positions, and surroundings. As a result, designers are able to focus on refining their design while still taking into account the environmental influence over time in a convenient way. The proposed platform will work as an analysis interface for the ongoing LightSolve project at MIT Daylighting Lab.