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structures or mechanisms that they are familiar with in order to write the code. Such
a simulation is, in effect, an abduction with respect to these underlying structures
and mechanisms—the phenomena are seen through these and expressed using them.
Finally, a reader of the simulation may not understand the limitations of the
simulation and make false assumptions as to its generality. In particular, the
inference within the simulations may not include all the processes that are in what
is observed—thus, it cannot be relied upon to either predict outcomes or justify any
specific explanation of those outcomes.

4.5.3 Mitigating Measures

As long as the limitations of the description (in terms of its selectivity, inference and
biases) are made clear, there are relatively few risks here, since not much is being
claimed. If it is going to be useful in the future as part of a (slightly abstracted)
evidence base, then its limitations and biases do need to be explicit. The data,
evidence or experience it is based upon also need to be made clear. Thus, good
documentation is the key here—one does not know how any particular description
will be used in the future, so the thoroughness of this is key to its future utility.
Here, it does not matter if the evidence is used to specify the simulation or to check
it afterwards in terms of the outcomes, all that matters is that the way it relates to
evidence is well documented. Standards for documentations (such as the ODD and
its various extensions (Grimm et al. 2006, 2010) help ensure that all aspects are
covered.

4.6 Illustration

4.6.1 Motivation

Sometimes one wants to make an idea clear, and an illustration is a good way of
doing this. It makes a more abstract theory or explanation clear by exhibiting a
concrete example that might be more readily comprehended. Complex systems,
especially complex social phenomena, can be difficult to describe, including
multiple independent and interacting mechanisms and entities. Here a well-crafted
simulation can help people see these complex interactions at work and hence
appreciate these complexities better. As with description, this purpose does not
claim much; it is just a medium for the communication of an idea. If the theory is
already instantiated as a simulation (e.g. for theoretical exposition or explanation),
then the illustrative simulation might well be a simplified version of this.
Playing about with simulations in a creative but informal manner can be very
useful in terms of informing the intuitions of a researcher (Norling et al. 2017).