  Presently, a very large number of public and private data sets are available
around the local governments. In most cases, they are not semantically
interoperable and a huge human effort is needed to create integrated ontologies
and knowledge base for smart city. 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, the management of the complexity and reasoning. In
this paper, a system for data ingestion and reconciliation smart cities related
aspects as road graph, services available on the roads, traffic sensors etc.,
is proposed. The system allows managing a big volume of data coming from a
variety of sources considering both static and dynamic data. These data are
mapped to smart-city ontology and stored into an RDF-Store where they are
available for applications via SPARQL queries to provide new services to the
users. The paper presents the process adopted to produce the ontology and the
knowledge base and the mechanisms adopted for the verification, reconciliation
and validation. Some examples about the possible usage of the coherent
knowledge base produced are also offered and are accessible from the RDF-Store.
