A Linked Data-Based Semantic Information Model for Smart Cities

Smart cities typically involve a myriad of interconnected systems intended to promote better management of urban and natural resources of cities, thereby contributing to the improve the quality of life of citizens. The heterogeneity of domains, systems, data, and relationships among them requires defining a data model able to express information in a flexible, extensible way while promoting interoperability between systems and applications. Furthermore, smart city systems can benefit from georeferenced information to allow for more effective actions over the real-world urban space. Aiming at tackling challenges related to data heterogeneity while considering georeferenced information, this work introduces LGeoSIM, a semantic-based information model for smart cities as means of fostering interoperability and powerful automated reasoning upon unambiguous information. LGeoSIM relies on the recent NGSI-LD Specification, thereby encompassing the principles of Linked Data to allow semantically defining information through ontologies and their interconnection. This paper also presents an implementation of LGeoSIM within Smart Geo Layers, a geographic-layered data middleware platform conceived to integrate data provided by heterogeneous sources in a smart city environment.