We need domain knowledge and understanding to build System dynamics models. If we capture domain knowledge which is also sensitive to System dynamics primitives then this model can be easily converted into a system dynamics model. How can we approach building such a domain knowledge model which can generate system dynamics model? This process must be automated eventually.
It is not a good idea to build one off models. We need to define a generic way of automatically generate system dynamics model. This requires that we capture domain knowledge in such a way that it is not only rich in knowledge of the domain, but also captures the primitives of system dynamics or any modeling paradigm for that matter. So far we have been taking domain knowledge to modeling paradigms. Lets take modeling paradigms to domain knowledge now.
I think your initial reference, must be the inference engine that uses the Semantic Web.
From there, go about building feedback loops system dynamics model, based on the rules that go finding.
Use data models based on ontologies
Very interesting question followed by nice overviews. I think systems dynamics emerge from the very root of "systems thinking", everything else is incidental. It is up to someone to enter,contribute and exit from such scenario, but the issue would remain as complex ever.
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