"This Is What We Don't Know": Treating Epistemic Uncertainty in Bayesian Networks for Risk Assessment.

ABSTRACT: Failing to communicate current knowledge limitations, that is, epistemic uncertainty, in environmental risk assessment (ERA) may have severe consequences for decision making. Bayesian networks (BNs) have gained popularity in ERA, primarily because they can combine variables from different models and integrate data and expert judgment. This paper highlights potential gaps in the treatment of uncertainty when using BNs for ERA and proposes a consistent framework (and a set of methods) for treating epistemic uncertainty to help close these gaps. The proposed framework describes the treatment of epistemic uncertainty about the model structure, parameters, expert judgment, data, management scenarios, and the assessment's output. We identify issues related to the differentiation between aleatory

SUBMITTER: Sahlin U 

PROVIDER: S-EPMC7839433 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature