A Semantic Query Component for Smart Cities
Smart cities, Linked Data, Semantic Web, Semantic Query
Smart cities are composed of several interconnected systems, designed to promote better management of urban and natural resources in cities, thus contributing to improving the quality of life of citizens. Data is of great importance for smart cities, as they significantly contribute to the strategic decision-making process for urban space. However, such a scenario is typically characterized by the high heterogeneity of data sources making the search for significant information more complex. To deal with these characteristics, ontologies have been used in conjunction with Linked Data to semantically represent information, infer new information from existing data and effectively integrate connected information from different sources. This scenario requires a data management strategy that includes efficient mechanisms to support information filtering and knowledge discovery. In this context, this work proposes a search component to semantic data based on the representation of georeferenced information in smart cities through ontologies and linked data. The proposed solution was applied to geo-referenced educational data from a city to infer new non-explicit information from existing data and relationships.