Building and updating a situational picture of the scenario under consideration is the goal of the Situation Assessment (SA) Information Fusion (IF) process. The scenario generally involves multiple entities and actors where possibly only a few under direct control of the decision maker. SA aims at explaining the observed events (mainly) by establishing the entities and actors involved, inferring their goals, understanding the relations existing (whether permanently or temporarily) between them, the surrounding environment, and past and present events. It is therefore apparent how the SA process inherently hinges on understanding and reasoning about relations. SA is a necessary preparatory step to the following phase of Impact Assessment (IA) where the decision maker is interested in estimating the evolution of the situation and the possible outcomes, dangers and threats. SA and IA processes are particularly complex and critical for large-scale scenarios with nearly chaotic dynamics such as those affected by natural or man-made disasters. This chapter will discuss recent developments in information fusion methods for representing and reasoning about relational information and knowledge for event detection in the context of crisis management. In particular, network methods will be analysed as a means for representing and reasoning about relational knowledge with the purpose of detecting complex events or discovering the causes of observed evidence.
