Integrating Streaming Data into Semantic Mashups

AbstractStreaming data, i.e., frequently changing and potentially infinite data flows, are becoming more and more prevalent in today's interconnected world. In a Smart City context, for instance, citizens can access real-time information about a city's weather, pollution, or traffic conditions. However, turning vast real-time data streams into actionable knowledge poses significant challenges. For instance, heterogeneous data from varied sources needs to be normalized and integrated, ideally using a common structured vocabulary. Furthermore, to provide users with both real-time and aggregate views on the data, data stream access requires support for temporal operators. Finally, it is difficult for non-technical users to integrate and leverage streaming data. To tackle these challenges, we propose an extension of the Linked Widgets concept for the streaming data domain. In this paper, we outline a platform prototype for the creation of streaming data mashups that is currently under development and illustrate its potential by means of a use case based on city real time bike data from the city of Vienna