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Preliminary investigations and analyses for building assets’ renovation require considerable time and resources. Being able to assess, in advance and on a large scale, how to address these assets would allow reducing issues to existing buildings as a priority. This research project aims to demonstrate how a data-driven approach can help make informed decisions and better allocate available resources. Starting with a sample of 468 buildings constructed in the city of Bologna between 1945 and 1965, the study led to the creation of a comprehensive database consisting of 468 records and 211 fields, grouped into 16 macro-categories. These fields represent the catalogued characteristics for each building; 95 of them were directly surveyed, and 116 were derived from the processing performed on the first 95 attributes. Each building is associated with various types of information to provide an overall framework (e.g., technical, typological, morphological, etc.). At the end of the database development, queries were performed to assess both the construction characteristics of the building sample and the qualitative performance in terms of structural, energy, and planimetric distribution. The results provide an indication of the building and show how in-depth analyses can serve as the foundation for a decision support system (DSS).
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Stefanini et al. (2025) studied this question.
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