Digital Twins for decision making : the uncertain half of the Twin

Three main types of uncertainty relevant for digital twins are identified: (1) Model uncertainty, (2) State uncertainty and (3) Run time uncertainty. For balancing these different uncertainties three methods are discussed: (1) Kalman filtering, (2) sensitivity analysis, (3) experimental perturbance. The Digital Twin for decision making can be deployed in various ways. The advice is to use this as a tool within reactive policy problems and to include statistical uncertainty information in decision making. Uncertainty information can be used for preventive policy problems to indicate where knowledge and information is missing. For transformative policy problems, the DT will mainly serve as a means of communication in which the judgments of partners can be included.