Keywords
climate change adaptation; iPad application; Bayesian belief networks; stakeholder engagement
Location
Session H5: Systems Modeling and Climate Change: A Systematic Methodology for Disentangling Elements of Vulnerability, Adaptation and Adaptive Capacity
Start Date
16-6-2014 9:00 AM
End Date
16-6-2014 10:20 AM
Abstract
The aim of this study is to use touch-screen computer tablet technology (e.g. iPAD) and its interactive flight console capabilities (e.g. touch screen 'sliders') as an improved method to stakeholder driven climate change adaptation research. Climate change vulnerability and adaptation have strong human dimensions meaning that the experiences of stakeholders often plays an important role when assessing adaptation options and/or the determinants of adaptive capacity. Methods such as Bayesian belief networks {BBNs) can draw upon the extensive knowledge and beliefs of stakeholders in a straightforward manner yet are underpinned by a robust mathematical framework (i.e. Bayes theory). This is critically important for advancing climate change adaptation research and policy adoption. This project is borne out by the observed difficulty that stakeholders have, at times, displayed when assigning conditional probabilities to BBNs. This methodological step is recognised as the most difficult challenge when developing these knowledge-based models. In response to this, we have developed a computer tablet application (through the App2Adapt project), tailored specifically to improve elicitation of stakeholder-generated conditional probabilities. This app has been developed based on the experiences of the research team and through field-testing at different stages of the design process, including application to a real-world example. The development of this app and usage of this rapidly emerging technology in stakeholder engagement process will lead to significant improvement of using BBNs as a methodological approach to climate change adaptation research.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
App2Adapt: Using Tablet Technology to Elicit Conditional Probabilities for Bayesian Belief Network Modelling
Session H5: Systems Modeling and Climate Change: A Systematic Methodology for Disentangling Elements of Vulnerability, Adaptation and Adaptive Capacity
The aim of this study is to use touch-screen computer tablet technology (e.g. iPAD) and its interactive flight console capabilities (e.g. touch screen 'sliders') as an improved method to stakeholder driven climate change adaptation research. Climate change vulnerability and adaptation have strong human dimensions meaning that the experiences of stakeholders often plays an important role when assessing adaptation options and/or the determinants of adaptive capacity. Methods such as Bayesian belief networks {BBNs) can draw upon the extensive knowledge and beliefs of stakeholders in a straightforward manner yet are underpinned by a robust mathematical framework (i.e. Bayes theory). This is critically important for advancing climate change adaptation research and policy adoption. This project is borne out by the observed difficulty that stakeholders have, at times, displayed when assigning conditional probabilities to BBNs. This methodological step is recognised as the most difficult challenge when developing these knowledge-based models. In response to this, we have developed a computer tablet application (through the App2Adapt project), tailored specifically to improve elicitation of stakeholder-generated conditional probabilities. This app has been developed based on the experiences of the research team and through field-testing at different stages of the design process, including application to a real-world example. The development of this app and usage of this rapidly emerging technology in stakeholder engagement process will lead to significant improvement of using BBNs as a methodological approach to climate change adaptation research.
