Constructing Event Processing Systems of Layered and Heterogeneous Events with SPARQL

SPARQL was originally developed as a derivative of SQL to process queries over finite-length datasets encoded as RDF graphs. Processing of infinite data streams with SPARQL has been approached by using pre-processors dividing streams into finite-length windows based on either time or the number of incoming triples. Recent extensions to SPARQL can support interconnections of queries, enabling event processing applications to be constructed out of multiple incrementally processed collaborating SPARQL update rules. With more elaborate networks of queries it is possible to perform event processing on heterogeneous event formats without strict restrictions on the number of triples per event. Heterogeneous event support combined with the capability to synthesize new events enables the creation of layered event processing systems. In this paper we review the different types of complex event processing building blocks presented in literature and show their translations to SPARQL update rules through examples, supporting a modular and layered approach. The interconnected examples demonstrate the creation of an elaborate network of SPARQL update rules for solving event processing tasks.