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 are not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation and the management of the complexity. In this paper, a system for the ingestion of data for smart city related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows to manage a big volume of data coming from a variety of sources considering both static and dynamic data, this data is then mapped to a smart-city and mobility ontology and stored into an RDF-Store where this data 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. Keywords Smart city, knowledge base construction, reconciliation, validation and verirication of knowledge base, linked open graph.