Developing knowledge graph based system for urban computing

Everyday our living city produces a tremendous amount of spatial-temporal data, involved with multiple sources from the individual scale to the city scale. Undoubtedly, such massive urban data can be explored for a better city and better life, as what the urban computing community has been dedicating in recent years. Nevertheless, existing studies are still facing the challenges of data fusion for the urban data as well as the knowledge distillation for specific applications. Moreover, there is a lack of full-featured and user-friendly platform for both researchers and developers in urban computing scenario. Therefore, in this paper, we present an urban knowledge graph (UrbanKG) system to incorporate knowledge graph with urban computing. Specifically, the system introduces a complete scheme to construct knowledge graph for urban data fusion from Data layer to Construction layer. The system further develops the multiple layers of Storage, Algorithm, Operation and Applications, which achieve the knowledge distillation and support various functions to the users. We perform three representative and practical use cases and demonstrate the system capability of boosting performance in various downstream applications, indicating a promising research direction of knowledge-driven urban computing.