Big Data e Data mining per le strategie di riqualificazione dell’edilizia residenziale. Il caso di Milano (1945-1990)

Following the new socio-economic directions set by the Circular Economy, the existing building stock (1950-1990) must be the new ‘artificial landscape’ for a sustainable development of future human settlement. As pointed by the European Union since 2011, the refurbishment of existing buildings may represent the chance for the whole construction sector (research and economic). This comes together with a growing interest for innovative tools for a sustainable managing process. The quantitative aspect of the building stock poses strong difficulties not only in the refurbishment process (structure and energy saving) but also in the planning of maintenance interventions (ordinary and extraordinary) and in general in the management of real estate assets (strategic, administrative and operational). The tool for reordering the collected big data is the matrix of building types. The paper presents the results of the first phase of the research (data mining) relating to the strategies for the residential second half of the twentieth century building stock refurbishment. The activity focused on public housing in Milan designed and built between 1950s and 1980s.