The document outlines an event processing reference architecture, detailing various levels of event refinement from preprocessing to process refinement. It emphasizes the importance of assessing impact based on situation development and provides a framework for identifying and managing events. The architecture integrates user interfaces for visualization and feedback control mechanisms to enhance decision-making based on event data.

1. Event Processing Reference Architecture Event Processing Reference Architecture Working Group March 24, 2006 Submitted by: Tim Bass, CISSP Principal Global Architect TIBCO Software Inc.

2. Event Processing Reference Architecture 24 EVENT PRE-PROCESSING EVENT SOURCES EXTERNAL . . . LEVEL ONE EVENT REFINEMENT USER INTERFACE Event Processing (EP/CEP) DB MANAGEMENT Historical Data Profiles & Patterns DISTRIBUTED LOCAL EVENT SERVICES . . EVENT PROFILES . . DATA BASES . . OTHER DATA LEVEL TWO SITUATION REFINEMENT LEVEL THREE IMPACT ASSESSMENT LEVEL FOUR PROCESS REFINEMENT Adapted from JDL: Steinberg, A., & Bowman, C., Handbook of Multisensor Data Fusion, CRC Press, 2001

3. Summary of Event Processing (Event-Decision) User Interface Human visualization, interaction and situation management Level 4 - Process Refinement Decide on control feedback, for example resource allocation, event source and state management, parametric and algorithmic adjustments Level 3 - Impact Assessment Impact assessment, i.e. assess impact on the basis of situation development, recognition and prediction Level 2 – Situation Refinement Identify situations based on events relations, relational state estimation, etc. Level 1 – Event Refinement Identify and track events based on association, filtering, joins, correlation etc. Level 0 – Event Preprocessing Cleansing of event-stream to produce semantically understandable data Event Sources Level of Inference Low Med High Reference: Bass, T., Processing Patterns for PredictiveBusiness™, March 2006.

4. A Handful of References Ranadiv é , V., The Power to Predict , McGraw-Hill, 2006. Bass, T., Processing Patterns for PredictiveBusiness™ , Event Processing Symposium, Hawthorne, NY, March 2006. Luckham, D., The Power of Events , Addison-Wesley, NY, 2002. Hall, D. and Llinas, J., Handbook of Multisensor Data Fusion , CRC Press, New York, 2001. Bass, T., Intrusion Detection Systems & Multisensor Data Fusion, Communications of the ACM, pp. 99-105, Vol. 43, No. 4, April 2000.