Air Traffic Management (ATM) systems are complex socio-technological systems that consist of a large number of interconnected human and automated components that as a whole exhibit global (emergent) properties that are not obvious from the local, individual parts. As a result, it is not trivial to oversee how the overall process depends on the behaviors of the individual agents involved, and the way in which interactions are organized. In fact, minor aspects of the behaviors of the individuals (e.g., skipping a procedure due to high workload, or misinterpreting incoming communication due to discrepancies in beliefs) may have serious consequences at the global level, potentially resulting in incidents or even larger accidents; however, this may strongly depend on whether some other actors compensate for shortcomings of their colleague actors: this is often referred to as resilience. When studying the design of such resilient organizations, an important problem is that this relation between local and global behaviors is usually not so trivial, and difficult to analyze and predict. To study the behavior of such complex resilient systems in a detailed manner, approaches are needed that are able to deal with this complexity. This project aims at establishing interlevel relations between different models describing ATM. The following research questions will be addressed in this project: Which properties are required for the agents at local levels to ensure certain behavior at the global level? How can descriptions at a global level of the system be related to descriptions at local levels and the organization of interactions? How does the global organizational behavior emerge? Can descriptions be found of the behavior at the global level that approximate the behavior of the local elements combined, but abstract from the local details? Which weaknesses in the organization can be identified?