A semantic search component for smart city applications - Silva, Larysse Savanna Izidio da (2020)
Smart cities are composed of several interconnected systems, designed to promote better management of urban and natural resources in cities, contributing to improving the quality of life for citizens. Data is very important 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 semantic search component based on the representation of georeferenced information in smart cities through ontologies and Linked Data. The semantic search component allows inferring new, non-explicit information from existing data and relationships. Experiments were performed with real-world smart city data to verify both effectiveness and efficiency of the proposed semantic search component.