Hybrid Computational Steering for Dynamic Data-driven Application Systems

We consider steering of Dynamic Data-Driven Application Systems from two sources, firstly from dynamic data and secondly via human intervention to change parameters of the system. We propose an architecture for such hybrid steering and identify a Time Manager as an essential component. We perform experiments on an actual realisation of such a system, modelling a water distribution network, to show how the parameters of the Time Manager can be determined.