Data-driven urban policies have gained attention from both private and public sectors. Digital technologies have permitted the collection and processing of large amount of data, especially the geographical one: the narrative of “Smart Cities”, together with the concept of “Big Data” offered new ways of studying urban phenomena through the measurement and visualisation of urban features (directly or indirectly).
Although new insights on modern cities emerged from this approach, many scientists have warned about an overly-optimistic trust on data, whose accuracy has been reported to be debatable [1]. In addition, using only quantitative data to study our cities might bring flat redefinitions thereof, where important qualitative insights (e.g. geographical, historical) find no place. Similar data-driven approaches to urban studies were also presented in the past; however, they were motivated by objectives of social justice and progressive social-economic reform [2]: today, smart cities’ practices and services are mostly connected to modes of profit-making rather than welfare and better wealth redistribution.
