With increasing demands for agility and reactivity of industrial and manufacturing processes, scientific circles and leading ICT (information and communications technology) companies have paid a lot of attention to EDA (event-driven architecture) and CEP (complex event processing). EDA and CEP enable event-driven systems -systems in which actions result from business events 3. Despite the recognized need for support of events to improve factory automation, signal processing, data acquisition, manufacturing, and other applications of industrial electronics, the use of EDA and CEP approaches in real-world solutions remains limited. One of the reasons for this is insufficient support for semantics in capturing and defining of complex events (CE) 20. Existing EDA and CEP approaches do not take into consideration different expressivity requirements that are needed in definition of a large number of diverse CE. We observe that semantic descriptions providing effective and expressive models for understanding of CE structures and their processing can be very helpful. In this paper, we show how achievements in the field of semantic technologies can contribute to the field of CEs and their support in information systems, especially from the point of view of their definition and processing. We present a framework that enables highly expressive event models and is based on ontologies and the Web Ontology language (OWL). We see ontologies and ontology representation languages as an opportunity to effectively deal with CEs in EDAs. Ontologies intrinsically provide a means for highly expressive semantic descriptions. In our framework, they are used to semantically describe CEs through conceptualizations of member events they are composed of. An important characteristic of our approach is that existing information that is captured in ontology can be reused in event detection and thus a wider scope of information can be taken into consideration when determining whether a CE should be triggered. Furthermore, ontologies enable hierarchical definitions of CEs and event taxonomies, which facilitates working with events on different levels of abstraction. If not all information for determining the exact subclass of event is available at a certain point of time, their generalizations can be used in order to increase the level of proactive behaviour of the overall system. When the information is added to the ontology their specializations are derived and used automatically. We use the OWL as the ontology representation language, because it provides a very appropriate foundation for CE definitions and has a wide support for reasoning. We propose a service that makes part of an EDA and enables translation of event data to OWL, detection of CEs and their triggering. It can act as an event source and as an event sink, which makes our approach complementary to existing approaches to support CEs that require higher expressivity and semantic descriptions. Our framework has been used in a case study project for electrical distribution domain, where it has been shown to be very useful and has improved the overall system flexibility and reactivity.
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