Improving risk characterisations in practical situations by highlighting knowledge aspects, with applications to risk matrices
本文提出一套实用方法，通过引入知识强度判断、风险因素排序和假设分析来改进风险矩阵等传统风险表征方法，特别关注当前知识可能带来的意外情况。
Current practice for risk characterisations is based on methods reflecting threats, their consequences and probability, as well as concepts like risk factors and sources. The risk matrix is an example of such a method. The risk analysis field has demonstrated that there are many challenges related to this practice and there is a substantial potential for improvements in how the characterisations can be conducted. The key is to better reflect the knowledge aspect of risk. The purpose of the present paper is to present a set of practical methods that can be used for characterising risk in this setting in line with these findings of the risk analysis field. Extended risk matrix approaches are highlighted. These approaches include strength of knowledge judgements and rankings of risk factors and assumptions supporting the analysis. Special attention is given to potential surprises relative to the current knowledge. Simple examples are presented to illustrate the use of these methods and approaches.