The research builds upon the different experiences and knowledge transfer concerning the urban qualities and indicators related to them. It expands the approaches to assessing the quality of open urban places by exploring the impacts of individual urban elements, spatial characteristics, and urban settings on users and their perception of quality. The concept connects urban places and related spatial identity with their uses as well as incorporates places’ social, cultural, historical, and, ultimately, economic dimensions, which steer their development. The complexity of such approach requires a considerable stock of knowledge and particularly involves the ever-present need for a multitude of information and data, which can describe a situation/conditions/state and predict or model its evolution.
COBISS.SI-ID: 3860356
The research project proposes novel methodologies to support integrating, optimising, and capturing heterogeneous neighbourhood-scale data, with application to decision-making in renewal and sustainability improvements of Slovenian neighbourhoods and settlements. Following our foregoing research where relevant sustainability metrics were sought to be integrated into a common sustainability performance index for the assessments of neighbourhood units, we continue with the most persistent issues encountered while continuously pursuing data-supported decision making. Here, we consider the collaboration between urban sciences and computer sciences as essential. In Slovenia particularly, the research that links architectural and urban subjects with advanced computer technologies has been so far rare. Linking is mostly limited to conventional IT support to certain tasks (GIS support, BIM design, 3D visualization, 2D rendering, and similar); however, there is little research that would present a mutual challenge ? both in spatial and related sciences and in terms of information technology solutions and methodologies processes (artificial intelligence, machine learning, algorithmic design, etc.).
COBISS.SI-ID: 3860868