TU Delft expert judgment data base

We review the applications of structured expert judgment uncertainty quantification using the "classical model" developed at the Delft University of Technology over the last 17 years (Cooke, 1991). These involve 45 expert panels, performed under contract with problem owners who reviewed and approved the results. With a few exceptions, all these applications involved the use of seed variables; that is, variables from the experts' area of expertise for which the true values are available post hoc. Seed variables are used to (1) measure expert performance, (2) enable performance based weighted combination of experts' distributions, and (3) evaluate and hopefully validate the resulting combination or "decision maker". This article reviews the classical model for structured expert judgment and the performance measures, reviews applications, comparing performance based decision makers with "equal weight" decision makers, and collects some lessons learned. Acknowledgement: The authors gratefully acknowledge the contributions of many people who cooperated in developing this database. Willy Aspinall, and Tim Bedford are independently responsible for a quarter of the studies. Introduction The pro’s and con’s of different weighting schemes remain a subject of research. The European Union contracted the TU Delft to review its applications both within EU projects, and elsewhere, in which experts assessed variables in their field of expertise for which the true values are known, in addition to variables of interest (Goossens et al 1996, 1998). These are called seed, or calibration, variables. Since then, the TU Delft expert judgment data base has nearly doubled. We now have studies involving over 67,000 experts' subjective probability distributions. The main sectors and summary information are given in Table 1 below. Table 1 Summary of applications per sector Sector # of experts # of variables # of elicitations Nuclear applications 98 2,203 20,461 Chemical ind. & gas industry 56 403 4,491 Groundwater / water pollution / dike ring / barriers 49 212 3,714 Aerospace sector / space debris /aviation 51 161 1,149