Game theoretical methods have been used for spectral awareness, space situational awareness (SSA), cyber situational awareness (CSA), and Intelligence, Surveillance, and Reconnaissance situation awareness (ISA). Each of these cases, awareness is supported by sensor estimation for assessment and the situation is determined from the actions of multiple players. Game theory assumes rational actors in a defined scenario; however, variations in social, cultural and behavioral factors include the dynamic nature of the context. In a dynamic data-driven application system (DDDAS), modeling must include both the measurements but also how models are used by different actors with different priorities. In this paper, we highlight the applications of game theory by reviewing the literature to determine the current state of the art and future needs. Future developments would include building towards knowledge awareness with information technology (e.g., data aggregation, access, indexing); multiscale analysis (e.g., space, time, and frequency), and software methods (e.g., architectures, cloud computing, protocols).