Architecture and Knowledge Modelling for Smart City

This thesis presents and details a smart-city ontology, called KM4City that is a knowledge model for the city and its data. The knowledge model pursues the objective of interconnect data gathered in the city, to transform it into semantically interoperable information. In fact, a variety of Open/Closed Data information sources are available from public administrations ranging from structural, statistical to real-time information. In most cases, this information has different formats, presents inconsistencies, incompleteness, and their semantic description is not sufficient to automatically compose them to have integrated global information of the area. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation (essential in order to effectively interconnected data to each other), the management of the complexity, to allow the data reasoning. In this thesis, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is also proposed. The system allows managing a big data volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to the presented KM4City ontology, and stored into an RDF-Store where they are available for applications via SPARQL queries, to provide new services to the citizens via specific applications of public administration and enterprises. In this thesis, the results that could be obtained by applying the ontology created, are also shown, which allowed to combine all data provided by the city of Florence and the Tuscany region including: maps, traffic status, weather conditions and forecast, parking status, real time sensors on public and private vehicles, point of interests in the city as museums, monuments, restaurants, hotels, hospitals, etc. but also statistical data like travel accidents, per street per year. Finally, an application that take advantage of the created repository and ontology, will be shown, which implement new integrated services related to mobility. The dissertation also presented the work performed about reconciliation algorithms and their comparative assessment and selection. The KM4City ontology realized in this thesis, has also been involved in the activity of DISIT lab mainly related to a number of smart city projects, especially among them Sii-Mobility which aims at collecting and exploiting data by solving the above mentioned problems and providing integrated data to be used for implementing smart city services for citizens mobility, public administrations, and SMEs.