Big Data – Spatial Experiment 02

(April 2015) This research project investigates the use of a large set of data in the design process with the aim of analysis and production of new types of spaces in the built environment. The research involves the observation of big-data driven projects and the production of a series of spatial prototypes. The research methodology involves analysis of case studies and production of spatial prototypes. The outcome of the analysis is the creation of knowledge about big-data driven projects to inform the design tests. The production of spatial prototypes allows for the investigation of the design process at its core. Large sets of data are acquired externally or produced internally and translated into point clouds which inform the creation of space. The final outcomes of these tests are objects, rooms or hybrid spaces of variable scale.

This test illustrates both a series of spaces generated with specific application to the scale of retail shops and the workflow which generates them. The process consists of: (a) collection of data about the use of (interior) space gathered through sensors and tracking devices, (b) conversion of data into point clouds and points into space (a parametric sphere generated from each point and subtracted from a solid mass). The resulting space is parametrically optmised and fitted into the existing room used as case study. If data about users’ preferences and the use of retail space are available, such information can be utilsed to improve the consumers retail experience by building a space which accommodates their preferences and requirements.