Ep-sparql: a unified language for event processing and stream reasoning

Streams of events appear increasingly today in various Web applications such as blogs, feeds, sensor data streams, geospa-tial information, on-line financial data, etc. Event Process-ing (EP) is concerned with timely detection of compound events within streams of simple events. State-of-the-art EP provides on-the-fly analysis of event streams, but cannot combine streams with background knowledge and cannot per-form reasoning tasks. On the other hand, semantic tools can effectively handle background knowledge and perform rea-soning thereon, but cannot deal with rapidly changing data provided by event streams. To bridge the gap, we propose Event Processing SPARQL (EP-SPARQL) as a new language for complex events and Stream Reasoning. We provide syntax and formal semantics of the language and devise an effective execution model for the proposed formalism. The execution model is grounded on logic programming, and features effective event process-ing and inferencing capabilities over temporal and static knowledge. We provide an open-source prototype imple-mentation and present a set of tests to show the usefulness and effectiveness of our approach