Data Science + Architecture

The architectural practice has often been at the forefront of technology, but when computer programmers began parameterizing design, the architects fled to the opposite side of the spectrum, stating that these cold machines could never design the same way a human hand could. Instead of viewing this historically polarized divide between computation design and traditional architectural design as unfavorable, architects can allow these technologies to inform their design practice — not overrule it.

Most architecture firms today create a digital model of their building, allowing architects to draft iterative models to analyze wall thickness, square footage, or building envelope information, but not the urban context. These models live in a closed-off silo from the surrounding context — yet we know these buildings when constructed will live in a context somewhere.

This practice does not allow an architect to visualize how their design might react to hurricane based flooding if it is along the Eastern Coast. A data scientist can bring clarity to this practice by creating custom data models to analyze flood planes, or helping to understand city evacuation routes in case of emergency. These tools are available to architects as more data becomes available — new insights do too!