Obtaining context sensitive information about the environment can be of great value for business applications to monitor, analyse and control their processes in real-time. Areas of application are for example logistics, manufacturing, retailing or power plants. Emerging technologies, like RFID, allow even small items of interest to be equipped with digital information. Sensors measure environmental conditions like temperature, pressure or pollution and GPS can be used for locating moveable objects. The generated data has to be processed by an information system. The concept of complex event processing (CEP) allows to do this asynchronously. Furthermore, events can be correlated to derive knowledge about situations of interest. However, centralized CEP systems have only limited scalability what impedes their use in distributed systems with many event input sources. Also a large variety of CEP systems exists on the market so that systems belonging to dierent business domains in most cases cannot interact. To overcome these drawbacks of centralized CEP systems a distributed CEP system is introduced that makes use of available, heterogeneous CEP technologies. This diploma thesis is part of the Distributed Heterogeneous Event Processing (DHEP) project involving IBMR Research & Development Boblingen and the University of Stuttgart. The project aims for providing a framework for distributed, heterogeneous event processing with focus on enterprise systems. The speci c contribution of this thesis is to integrate the context information of a business domain into the DHEP system. That means a data model must be available that describes the environment (e.g. information about location, people, goods, tools, enterprise structure) and enables to interpret the data from input sources in the current context. For the description of such data models industry standards exist in dierent domains that use concepts from complex object modelling languages, like UML or OWL for example. Based on such descriptions corresponding executable code and data structures can be generated. These artefacts are used to enrich primitive events from sensors or other input sources with higher level information and make it accessible for distributed, heterogeneous CEP.