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Probably the most difficult type of uncertainties to deal with, are the uncertainties that are caused by a lack of knowledge. It is possible that a cause-effect chain includes some steps on which no (or hardly any) quantitative information is available. In accordance with the precautionary principle, the modeling of such parts of the cause-effect chain has to be based on a worst-case assumption. Preferably this assumption is based on expert judgment. Unless experts are able to estimate the uncertainty margin of the assumed relation too, the probabilistic modeling approach will be similar to the deterministic approach (for this part of the cause-effect chain).

In case of a lack of knowledge, analyzing the sensitivity of the final results on the possible shapes of the unknown relation will be useful. If the finally predicted impact turns out to be very sensitive to the unknown factor, further research to this topic should be recommended. 

Also see Tool - Visualising and managing uncertainties and EDD - Governance - Knowledge context for strategies on how to deal with uncertainties due to a lack of knowledge.