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Big cities are heterogeneous environments in which socioeconomic and environmental differences among the neighborhoods are pronounced, therefore research projects that aim at informing public health policies at a single city level are being developed. Since most of public health data is referred to some geography, spatial enablement plays a fundamental role when it comes to analysis and visualization of urban health data. The PULSE project, part of the EU Horizon 2020 framework, involves five cities to transform public health from a reactive to a predictive system, and promote wellbeing by developing an integrated data ecosystem based on continuous large-scale collection of information, leading to better-informed data-driven health policy. One of the goals of PULSE is to apply spatial enablement to generate statistics useful to asses public health at a high spatial resolution, allowing to organize interventions at a neighborhood level. In this paper, we present a preliminary spatial enablement study carried out in this context, in which we show opposite sides of its application: while the results are promising, the lack of standardization and protocols in the data collection and representation processes make spatial enablement very difficult to apply to open data.

Advantages and Difficulties of using Spatial Enablement to Support Public Health in Cities: The PULSE Case Study