Mappare il benessere sociale attraverso il GIS ed il confronto di diversi casi di studio

The research project is based on the possibility to enhance a region by its proper management, helping in generating local community well-being, reconstructing the dual dimension of territory and governance quality, especially related to scientific and institutional innovation. Enhancing the territory by its proper management means testing the differences between the innovation capacities of its governance and the territorial impacts of these differences. The hypothesis is that there is a functional relation between territorial resources and social capabilities processes. It is possible to verify the relationship between characters acquired by the territory and social characters of regional governance through the implementation of social wellbeing indicators in a comparison between different countries local contexts. Along with the skills, the levels of well-being increase as well: therefore, the GDP analysis is no longer efficient in assessing the national production and the individual income as a surrogate indicator of well-being conditions, while a more appropriate analysis should rather consider the quality of services and the quality of life which will advance the deployment of public services and their environmental sustainability. The analysis of eco-systems services, like public green quality or urban development quality, introduces the local resources balance concept, that tries to reach a sustainable development model based on Bruntland Report, where the "present generations have the ability to ensure the standard of well-being at least equal to the current". This brings to the evidence the collective interest in assuring resources reproducibility. In order to implement and test this sustainable concept of well-being, we think that a very important step is the knowledge of the territory and of the governance of the case study area: for this reason we propose the collection and spatial representation of all the information layers of the data that provide information for the building of the well-being indicators set, that will be as well represented in maps. To this purpose we will compare traditional geo-referred maps, with more abstract spatial maps like chorems, etc. showing the relations and the weights of the well-being indicators in the model. The final objective is to evaluate different country case studies with different local contexts, using a visual approach, comparing the maps of the well-being indicators.