SPARQL-Based Applications for RDF-Encoded Sensor Data

Complex event processing is currently more dominated by proprietary systems and vertical products than open technologies. In the future, however, internet-connected people and things moving between smart spaces in smart cities will create a huge volume of events in a multi-actor, multi-platform environment. End-user applications would benefit from the possibility for open access to all relevant sensors and data sources. The work on semantic sensor networks concerns such open technologies to discover and access sensors on the Web, to integrate heterogeneous sensor data, and to make it meaningful to applications. In this study we address the question of how a set of applications can efficiently access a shared set of sensors while avoiding redundant data acquisition that would lead to energy-efficiency problems. The Instans event processing platform, based on the Rete-algorithm, offers continuous execution of interconnected SPARQL queries and update rules. Rete enables sharing of sensor access and caching of intermediate results in a natural and high-performance manner. Our solution suggests that with incremental query evaluation, standard-based SPARQL and RDF can handle complex event processing tasks relevant to sensor networks, and reduce the redundant access from a set of applications to shared sensors.