Computational Urbanism a is digital and contemporary approach to masterplanning seeking data-driven form-finding methods in the scale of urban design. Although the approach is site-less, a case study was made in a specific location in East London. Sound data was used as the main driver behind form-finding and site-selection. The dataset-driven iterations to geometrical volumes were investigated. The main 3 subjects of investigations were shape/size (XYZ), geo-location and density. The aim of the approach is to highlight countless iterations and possibilities there is to a design problem/opportunity, yet designer's role and purpose remains as the catalyst between data, computing and intuition.
The ability of human mind to handle larger urban complexities is improving each day, thanks to the human’s role-shifting from the processor to the conductor. At this point, we should widen the topic of “complexity” to estimate the possibilities of inventing new interfaces between cities and users. Batty defines “complex systems” in an extremely basic way as systems consist of other complex systems. Then he exemplifies it with two topics; economies and cities, where both are highly complex, yet both connected with other upper complex systems. (Batty, 2007) If we interpret the same approach to urban scale, the results would be a correspondent. “Artifacts that we build to give physical representation to cities can also be so partitioned into their component parts,” says Batty, when defining the city as a complex system. (Batty, 2007)
The slightly new role of the human mind to be a conductor of multiple tools that can process different data sets creates the opportunity to handle urban complexities by running up-to-date digital tools simultaneously. In the past, when the human mind was the processor, each individual covered a limited amount of process, and each process had a limited amount of directions to follow simultaneously, because of the natural limitations. Nevertheless, the processor was an organic being. This caused a gap between the data that exist and the data that can be processed. (Leach, 2009)
Presently, thanks to the simultaneity supplied by the shifting of the human’s role in data processing, new expression methods could be generated to reveal more of the information driven by the big data. (Chandler 2015) In other words, the interface between raw data and observer has the chance to evolve into things which have more depth and sophistication inside.
