Can big data help make demolition more democratic?
In this short piece Yikun Fang explores the perception of demolition in the city, and questions the speed of urban change. Yikun is a current Master of Research in Architecture student at the Royal College of Art.
Through my historical research on Shanghai, I explored the issue of building demolition throughout the city’s development. The reasons for demolition are often cited as rational: the city needs to expand, and the old buildings cannot meet the current needs of people. The reason for not demolishing is perceptual. People have lived here since childhood and have good memories of this place.
In order to mediate the contradiction between sensibility and rationality, I turn to use the method of big data to examine demolition in Shanghai. I begin by creating a dataset of ‘high-value architecture.’ High-value architecture here refers to buildings often mentioned in social Gaode map, often found on search engines and maps. After a visitor searches and checks in at a location, the platform’s rating system allows visitors to score, calculate the average score and update it on the map in real-time.
I use this as a proxy of people’s attachments and values towards these buildings, suggesting these might be important buildings in people’s memory. If these buildings are demolished one day, how could we calculate an optimal the demolition method? If important buildings, or meaningful buildings can be demolished slowly, it means people have more time to adapt to change. This could, I argue, alleviate some of the problems of collective memory caused by the fast speed of blasting demolition.
