City Crawlers Berlin

Cities can be viewed as information architecture systems. The term makes sense not in reference to the the design of buildings, but rather to the components of a complex system that interact with each other. In a paper written by L.A. Coward and N.A. Salingaros in 2004, the authors explore this topic. They argue that a city is less like an electronic computer, but more like a human brain. ‘A city heuristically defines its own functionality by changing connections so as to optimize how components interact’.

This information exchange, using the infrastructure of a city, can include the movement of people and goods, personal contact and interactions, and telecommunication and visual input from the environment. As with the information architecture of the brain and computers, the network has nodes, connections and interrelationships. At a higher level, people or groups, or groups of people, move from one function to another. Goods are moved, consumed, changed, combined, and created in a city. And exchanging information is cheaper than moving people and goods. So how does a city like Berlin efficiently coordinate different exchanges of different costs? Maybe mapping them is way to find out.

A half hour trip by public transport has a cost and a value. The same goes for a restaurant. Some restaurants become focal points for information exchange in a city, which are often identified with a certain business in a large metropolitan area. By being at a certain place, the restaurant becomes a significant node in the town’s social and government networks. Coward and Salingaros make an interesting argument: ‘When nodes do not form part of a larger module, they are often parasitic to the city, since they use its infrastructure without contributing to an overall functional coherence‘.

By looking at data, we hope to identify the system architecture of Berlin by visualizing complex networks. And by doing that, we hope to contribute to a model of a smart city that is able to adjust itself like a living organism. Salingaros concludes: ‘Rather than using models based on visually regular aerial geometries, this approach makes it possible to evaluate changes to city plans, zoning codes, transportation and communication networks in terms of their impact on overall city effectiveness‘.