A huge amount of information is generated from the rapidly increasing number of sensor networks and smart devices, generating and publishing information in multiple formats, thus highlighting interoperability as one of the key prerequisites for the success of the Internet of Things (IoT). The BT Hypercat Data Hub provides a focal point for the sharing and consumption of available datasets from a wide range of sources. In this work, we present a semantic enrichment of the data hub, using a number of widely-used Semantic Web standards and tools.
The system has been successfully deployed as part of two use cases. The SimplifAI project is aimed at urban tra c management and control in order to reduce tra c and improve air quality. The BT Hypercat Data Hub was utilized for automated semantic enrichment of imported IoT data. In addition, City Concierge is a use case of the CityVerve project aiming to increase uptake of walking and cycling as a preferred travel mode in Greater Manchester. The data hub provides the required infrastructure and functionality in order to enable the City Concierge through the aggregation and exposure of city IoT information. 2
Conclusion The semantic enrichment of the BT Hypercat Data Hub has been presented. Future work includes further semantic enrichment by enabling GeoSPARQL queries. In addition, spatiotemporal reasoning is a prominent direction that could provide richer knowledge by combining data coming from both the BT Hypercat Data Hub and the LOD cloud.