Engaging stakeholders in construction and validation of Bayesian belief networks for groundwater protection

A Bayesian belief network (BN) for farming contracts has been constructed and validated with direct co-operation and in dialogue with stakeholders. On the one hand, BN’s can create space for an open dialogue with stakeholders due to the flexibility of the decision support tool. This allows factors (nodes), associations (directed links) and probabilities to be adjusted and validated throughout the process and based on inputs from all involved stakeholders and experts. On the other hand getting stakeholders to understand and accept the idea behind BNs is demanding. Especially the required probability assessments are not easy to understand by stakeholders. Copyright © 2004 IFAC

[1]  Kevin B. Korb,et al.  Bayesian Artificial Intelligence , 2004, Computer science and data analysis series.

[2]  E. Mostert PUBLIC PARTICIPATION AND THE EUROPEAN WATER FRAMEWORK DIRECTIVE , 2003 .

[3]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[4]  Mark E. Borsuk,et al.  Integrative environmental prediction using Bayesian networks: A synthesis of models describing estuarine eutrophication , 2002 .

[5]  H. Järvelä Agricultural economics research institute , 1983 .

[6]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[7]  Mark E. Borsuk,et al.  Integrated approach to total maximum daily load development for Neuse River Estuary using bayesian probability network model (Neu-BERN) , 2003 .

[8]  F. V. Jensen,et al.  The SACSO methodology for troubleshooting complex systems , 2001, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[9]  韓國 統計研究所,et al.  統計年鑑 = Statistical yearbook , 1973 .

[10]  B. Marcot,et al.  Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement , 2001 .

[11]  Silja Renooij,et al.  Talking probabilities: communicating probabilistic information with words and numbers , 1999, Int. J. Approx. Reason..

[12]  E. Mostert The challenge of public participation , 2003 .

[13]  Sakari Kuikka,et al.  Learning Bayesian decision analysis by doing: lessons from environmental and natural resources management , 1999 .

[14]  F. Haakh Protection of drinking water sources for quality and quantity---ground water and surface water , 2000 .

[15]  Silja Renooij,et al.  Probabilities for a probabilistic network: a case study in oesophageal cancer , 2002, Artif. Intell. Medicine.

[16]  Finn Verner Jensen,et al.  MUNIN: an expert EMG assistant , 1988 .

[17]  Silja Renooij,et al.  Evaluation of a verbal-numerical probability scale , 2003, Int. J. Approx. Reason..

[18]  Bruce Abramson,et al.  Using belief networks to forecast oil prices , 1991 .

[19]  Manuel Gómez,et al.  Real-World Applications of Influence Diagrams , 2004 .

[20]  Sven Ove Hansson,et al.  Indicators of uncertainty in chemical risk assessments. , 2004, Regulatory toxicology and pharmacology : RTP.