The SICRaS Project

The idea behind the SICRaS project is that a deeper territorial knowledge and advanced decision support tools, running on such knowledge, may help policy makers and provide a contribution for a better public administration.

SICRaS aims at synthesizing (big) knowledge from the large amount of information collected by both public administrations and other public officers and organizations (e.g. notaries, public utilities and so on): this information is typically scattered over several heterogeneous and decoupled data sources and might also be partially outdated, unreliable and redundant. To realize its purpose, SICRaS leverages on:

  • semantic technologies, to provide a unified conceptual integration framework, as well as to implement advanced reasoning and analysis techniques on top of the knowledge provided by the data sources;
  • geo-spatial technologies, to exploit the notion of territory, seen as a spatial region in our ontological model; this enables new ways of extracting, observing and analyzing data about real world entities and the spatial relations among them.
  • a scalable system to reconcile identities to the same real world entity across datasets, associating a unique and persistent name to each single entity;

On top of the so obtained (big) knowledge, big analytic functions will be developed. To do so, we are integrating semantic technologies in the core of the SpagoBI suite. Big Analysis techniques will then be employed for facilitating tax and social processes with advanced intelligence functions such as, for instance:

  • Identifying behavioral patterns: identifying common traits of either recognized tax evaders or individuals suffering the same conditions of social exclusion’s risk;
  • Identifying citizens exhibiting specific behavior or characteristics: recognizing
    citizens that behave like known tax evaders or that may live in conditions of poverty;
  • Analyzing trends and predicting possible changes in the territory: analyzing
    social or fiscal relevant phenomena to predict their evolution in time and over the territory.

Such decision support functions will also take advantage of Spatial Business Intelligence (SBI) realized by integrating Geo-Spatial and Business Intelligence technologies. The combination of traditional and spatial data will allow us to employ spatial analysis and map visualization to o er innovative and groundbreaking intelligence solutions for local policy makers.

Beside tax and social applications, the SICRaS approach will open up to many other applications in different areas such as, for instance, mobility and tourism.

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