Towards unified and native enrichment in event processing systems

Events are encapsulated pieces of information that flow from one event agent to another. In order to process an event, additional information that is external to the event is often needed. This is achieved using a process called event enrichment. Current approaches to event enrichment are external to event processing engines and are handled by specialized agents. Within large-scale environments with high heterogeneity among events, the enrichment process may become difficult to maintain. This paper examines event enrichment in terms of information completeness and presents a unified model for event enrichment that takes place natively within the event processing engine. The paper describes the requirements of event enrichment and highlights its challenges such as finding enrichment sources, retrieval of information items, finding complementary information and its fusion with events. It then details an instantiation of the model using Semantic Web and Linked Data technologies. Enrichment is realised by dynamically guiding a spreading activation algorithm in a Linked Data graph. Multiple spreading activation strategies have been evaluated on a set of Wikipedia events and experimentation shows the viability of the approach.