1. Improvements in the Spatial and Temporal representation of the Model Owen Woodberry Bachelor of Computer Science, Honours

2. My part in this Process Honours Project –Knowledge Engineering a Bayesian Network for an Ecological Risk Assessment Knowledge Engineering Bayesian Networks –Difficulty of expert elicitation –Automated learning methods –Future development of the BN

3. Some application objectives Improving the spatial representation of the network Improving the temporal representation of the network Exploring the effects of combining experimental data with elicited values Evaluating the network Identifying other possible improvements

4. Overview Spatial Representation –Improved networks –Points for Discussion Temporal Representation –Improved networks –Points for Discussion Other questions regarding BN technology

5. Spatial Representation How can we improve the existing network? –Site/type dependent nodes –Site/type independent nodes Global representation of the system

6. Improved networks As it is now With an additional site node With an additional site and type node

7. Points for discussion What different collections of sites would be useful to consider as a type? Other spatial considerations not yet identified

8. Temporal Representation Management decisions will usually require consideration of future impacts A Bayesian Network usually represents a single time period The ideal network would be flexible enough to allow consideration of impacts across any time scale

9. Improved networks As it is now Collection of static networks for each time scale With an additional time scale node Dynamic Bayesian Network (Ideal)

10. Points for discussion For which links in the BN are these different time scales taking effect? How are the differing time scales affecting these links? How do you quantify these effects? Other temporal considerations not yet identified

11. Other questions regarding BN technology Incorporating of networks representing different species into a single network.