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itself. The other question is: How? Isn't modelling a technically-demanding task, requiring
specialist skills that we can't expect ordinary people to possess? Building models from scratch is;
but, given an appropriate interface (usually a diagram), stakeholders with no prior modelling
experience can quickly learn to 'read' the diagram and to comment on the objects and relationships
it contains. Maybe not at the level of the mathematical equations, but certainly at the conceptual
level.
So, in the context of ATEAM:
In the early stages of the project, stakeholders are shown the proposed model (at some appropriate
level of detail, through some appropriate filter), or possibly the proposed alternative models.
They are asked to comment on the nature of the models: What's been left out? Do the models
produce the outputs (indicators that are most relevant? If not, what changes need to be made to
incorporate these indicators? At a qualitative level, are the modelled relationships realistic? A
declarative modelling approach, with an appropriate visual interface, can make it much easier to
involve stakeholders in these important questions.
In the middle stages of the project, the model is run in the presence of stakeholders. They can
comment on the observed behaviour, and engage in a review of the model structure to explore
reasons for odd results. The researcher drives the computer, but the stakeholder is making the
suggestions.
At the end of the project, the stakeholder gets the model, ready to use with an interface that
enables alternative scenarios to be readily explored. This is not possible in the current ATEAM,
since each model is implemented using a different technology, and it would take a lot of work to
enable others to install the model, run it, and extract the results in a meaningful fashion. With a
clean separation between the model and the tools available for using it, a future ATEAM project
could enable people with little computing experience to select a model through their web browser,
be presented with a GUI (graphical user interface) generated on the fly for that model (including
input sliders and output graphs, tables and maps), and run the model. If they wished to drill down
into the model diagram and equations, they could do so.
9.3 Re-casting existing models in a declarative model-representation
language
The thought experiment presented here is based on the assumption that we are living in a
declarative-modelling world: all models are already represented in a declarative modelrepresentation
language, published on the web, and so on. But we don't, and they're not! So it is
appropriate to ask: How do we get there from here?
We need to be clear that declarative modelling is not simply some sort of wrapper we can put
around existing models. It is an entirely new way of representing the model. Therefore, existing
models will need to be re-cast in a declarative language. There are several points to make:
1. Already, considerable effort has been spent in re-writing existing (programmed) models in a
new language. For example, LPJ itself was originally written in Fortran, and has been totally
re-engineered in C++. Clearly, some groups do consider that it is worthwhile doing this - and
that is just from one procedural implementation to another. The benefits of re-casting a
model in a declarative language should provide a greater incentive to undertake the task, even
if only to save on the cost of maintaining and updating the existing programming.
2. If a model has been well programmed, with well-laid out equations, and suitable partitioning
off of sections concerned with updating state variables, then the effort needed to re-cast it in a
declarative style is not great (weeks, rather than months). Many of the equations can be lifted
as they stand.
3. If, on the other hand, the existing model code is poorly coded and difficult to disentangle, then
the effort required is greater, but the need is also greater. The scientific value of a poorlyprogrammed
model is very limited, since the essence of a model as part of the scientific