Retractable Complex Event Processing and Stream Reasoning Darko Anicic 1 , Sebastian Rudolph 2 , Paul Fodor 3 , and Nenad Stojanovic 1 1 FZI Research Center for Information Technology, Germany 2 AIFB, Karlsruhe Institute of Technology, Germany 3 State University of New York at Stony Brook, USA Abstract. Complex Event Processing (CEP) deals with processing of continu- ously arriving events with the goal of identifying meaningful patterns (complex events). In existing stream database approaches, CEP is manly concerned by tem- poral relations between events. This paper advocates for a knowledge-rich CEP with Stream Reasoning capabilities. Secondly, we address the problem of revi- sion in event processing. Events are often assumed to be immutable and therefore always correct. Revision in event processing deals with the circumstance that cer- tain events may be revoked. This necessitates to reconsider complex events which might have been computed based on the original, flawy history as soon as part of that history is corrected. In this paper, we present a novel approach for knowledge-based CEP and Stream Reasoning, including revisions of events too. We present a rule-based language for pattern matching over event streams with a precise syntax and the declarative semantics. We devise an execution model for the proposed formal- ism, and provide a prototype implementation. Extensive experiments have been conducted to demonstrate the efficiency and effectiveness of our approach. 1 Introduction While existing semantic technologies and reasoning engines are constantly being im- proved in dealing with time invariant domain knowledge, they lack in support for pro- cessing real-time streaming data. Real-time data on Web is valuable only if it is cap- tured, processed, and delivered instantly. Examples include traffic monitoring, real-time financial services, web click analysis and advertisement, various social web and real- time collaboration tools, and so forth. Complex Event Processing (CEP) is a set of techniques and tools that help us in understanding and controlling real-time and event-driven systems [11]. As such, it is a technology that can help in processing real-time data on the Web too. CEP deals with processing continuously arriving events with the goal of identifying meaningful event patterns (complex events). An event represents something that occurs, happens, or changes the current state of affairs. For example, an event may represent a stock price change, a complied transaction, a new piece of information, knowledge made available by a Web service, and so forth. In all these situations, to structure the course of affairs and describe more complex dynamic situations, we compose simple (atomic) events into complex events. Today’s CEP systems [1,13,4], however, focus on high throughput N. Bassiliades et al. (Eds.): RuleML 2011 - Europe, LNCS 6826, pp. 122–137, 2011. c  Springer-Verlag Berlin Heidelberg 2011