Abstract
New technologies allow for new ways to sense the city. Thinking of urban data as substance, this paper criticises a certain approach in dealing with urban-related data analysis when it comes to identifying certain patterns and deriving narratives based on these patterns. In this approach, coined here as the ‘big data’ approach, having access to large-volume datasets is considered sufficient to study a phenomena and its very dynamics that the data refers to. In contrast to this, this paper examines ways in which data can be produced, modified and delivered; in any of these steps, there is an ongoing cost–benefit analysis, based on which a series of necessary decisions in terms of resolution and quality of data through the lens of filtering has to be made with the goal of accessing data and making it accessible most effectively. Projects from MIT SENSEable City Lab are used to better illustrate these ideas.
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