Knowledge elicitation using more than one expert to cover the same domain

Moore, C. J.; Miles, John Christopher

doi:10.1007/bf00141757

Cited by 21 publications

(9 citation statements)

References 12 publications

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“…Finally, anchoring, overconfidence and inconsistency are frequent cognitive biases. The unifying feature of these biases is a deficient evaluation of evidence; causes include a human preference for familiarity (Moore and Miles 1991), insufficient (use of ) feedback (Fischer and Budescu 2005) and limited processing capacity (Halford et al 2007). It may be possible to control these biases by providing continuous and immediate feedback to experts about their use of available evidence (Knol et al 2010).…”

Section: Bias Uncertainty and Aggregation Of Expert Knowledgementioning

confidence: 99%

Toward rigorous use of expert knowledge in ecological research

et al. 2013

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Abstract. Practicing ecologists who excel at their work (''experts'') hold a wealth of knowledge. This knowledge offers a wide range of opportunities for application in ecological research and natural resource decision-making. While experts are often consulted ad-hoc, their contributions are not widely acknowledged. These informal applications of expert knowledge lead to concerns about a lack of transparency and repeatability, causing distrust of this knowledge source in the scientific community. Here, we address these concerns with an exploration of the diversity of expert knowledge and of rigorous methods in its use. The effective use of expert knowledge hinges on an awareness of the spectrum of experts and their expertise, which varies by breadth of perspective and critical assessment. Also, experts express their knowledge in different forms depending on the degree of contextualization with other information. Careful matching of experts to application is therefore essential and has to go beyond a simple fitting of the expert to the knowledge domain. The standards for the collection and use of expert knowledge should be as rigorous as for empirical data. This involves knowing when it is appropriate to use expert knowledge and how to identify and select suitable experts. Further, it requires a careful plan for the collection, analysis and validation of the knowledge. The knowledge held by expert practitioners is too valuable to be ignored. But only when thorough methods are applied, can the application of expert knowledge be as valid as the use of empirical data. The responsibility for the effective and rigorous use of expert knowledge lies with the researchers.

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Section: Bias Uncertainty and Aggregation Of Expert Knowledgementioning

confidence: 99%

Toward rigorous use of expert knowledge in ecological research

et al. 2013

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“…The use of multiple experts is discussed at length in the literature (McGraw & Searle, 1988;Moore & Miles, 1991;Medsjer et al, 1995). More recently, work by Keeney (2004), Boutilier (2005), Cowell et al (2005) and Detwarasiti and Shachter (2005) brings the discussion to the present.…”

Section: Previous Literaturementioning

confidence: 99%

Influence diagrams and multiple experts: a preliminary model

Hurt¹

2010

Expert Systems

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This paper examines the problem of eliciting expertise from multiple experts without using group techniques and then using that expertise in a meaningful manner. The solution proposed preserves the input of the experts in two problem areas: (1) where there is disagreement among the experts and (2) where there is unequal weighting of the experts. The model proposed has the benefit of robustness and of retaining the reliability and validity of the underlying expertise.

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“…Moore and Miles (1991) developed a three-stage knowledge elicitation process using more than one expert to cover the same knowledge domain. Their main reason for doing so was the problems involved in meeting with the single expert.…”

Section: Knowledge Engineering Processmentioning

confidence: 99%

“…In this section the authors look at the processes utilized to elicit knowledge from the experts in the domain of cost escalation to help with the development of the overall cost escalation model. Moore and Miles (1991) developed a three-stage knowledge elicitation process using more than one expert to cover the same knowledge domain. Their main reason for doing so was the problems involved in meeting with the single expert.…”

Section: Knowledge Engineering Processmentioning

confidence: 99%

A Decision Support System Specification for Cost Escalation in Heavy Engineering Industry

Dawood

Bates

2002

Computer aided Civil Eng

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The heavy civil engineering industry (railways, sewage-treatment, chemical and pharmaceutical facilities, oil and gas facilities, etc.) is one of the major contributors to the British economy and generally involves a high level of investment. Clients in this industry are demanding accurate cost estimates, proper analysis of out-turn cost and cost escalation, and a high quality risk analysis throughout the construction processes. Current practices in the industry have suggested that there is a lack of structured methodologies and systematic cost escalation approaches to achieve an appropriate cost analysis at the outset of projects and throughout the construction processes. In this context the prime objective of this research work is to develop a structured cost escalation methodology for improving estimating management and control in the heavy engineering industry construction processes. The methodology is composed of a forecasting model to predict cost indices of major items in industry and a risk knowledgebase model for identifying and quantifying causes of cost escalations. This paper reviews and discusses a knowledgebased model for applying a cost escalation factor. The cost escalation factor is made up of market variation, a risk element, and a component for bias. A knowledge elicitation strategy was employed to obtain the required knowledge for the model. The strategy included questionnaires, interviews, and workshops, and deliverables came in the form of influences and their effect on project cost escalation. From these deliverables, a decision support system and specifications for applying cost escalation to base estimates are presented.

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Knowledge elicitation using more than one expert to cover the same domain

Cited by 21 publications

References 12 publications

Toward rigorous use of expert knowledge in ecological research

Toward rigorous use of expert knowledge in ecological research

Influence diagrams and multiple experts: a preliminary model

A Decision Support System Specification for Cost Escalation in Heavy Engineering Industry

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