The composite event detection process in different consumption modes has been proven to be difficult to comprehend. It is believed that visualization of this process can make it easier to grasp. In this final year project, a prototype of a visualization tool that visually displays the composite event detection is developed. The prototype uses time graphs to display the composite events and the chronicle consumption mode is used in the detection of the composite events. Animation is used in the prototype when the composite events are visualized, as it is believed that animation can be of help when learning complex algorithms, such as consumption modes. The prototype is then compared with other similar visualization tools. This prototype addresses factors, which have been identified as playing a central role in the visualization of composite events, that other similar visualization tools do not.