Cyber-physical systems are context-aware networked systems containing sensors, aggregators and actuators. Raw sensor data and aggregated information are spread among the network and processed in multiple nodes to result in an action, which is possibly executed at a different physical location in the network. Due to the flexible topology and the emergent features of CPS, decisions within the network that trigger actions are not always trivial to understand. These decisions are based on raw sensor data which are not clearly visible at the location of their execution. This can be problematic if decisions have to be justifiable. It becomes even more difficult if decisions has been flawed, and it is not ascertainable why they were made. In order to determine the reasons for incorrect decisions in the network, the dependencies and input values of a decision must be known. Without this information, debugging is quite difficult. In this paper, we present the Information Flow Monitor, which can capture and visualize dependencies between nodes and information in CPS.