There are two parts to this question 1) how best compute differences
between models, and 2) how best to represent differences between
models?

Context:
I have a number of (instance) models, each sharing a common schema
(import), each in its own namespace, each representing one of multiple
simulation runs in a project analyzing a common situation.    Each
model represents a different experiment ( i.e.,  different
parameterizations) of a simulation model with results.  I am
translating existing simulations (proprietary format)  into OWL to do
this, so this is post-hoc analysis (the end goal is to handle model
variation when it happens in the application using owl, but I need to
deal with legacy simulations as well).     The difference between
models is very small (a handful of statements), because the engineers
are simply varying input parameters for risk analysis.  This is like
an SCM problem in the sense that I would like to create a model
derivation tree, but different because it is post-hoc, and I need easy
access to all the models for statistical aggregations (i.e., risk
analysis), else I could use an SCM. The objective is is to to save
space and gain referential integrity/normalization by for example, re-
organizing the models into a derivation tree .

Possible Solutions:
Are there tools within TBC that I could use to do this?   I will need
to identify the common substructure between the models, so that the
largest common submodel is the root of the derivation tree, and so
on.  What is the best way to 'diff' them, or find what is common
between them?    I could use imports to structure the derivation tree
or I could use SPARQL construct queries and Sparql Motion to represent
the derivation tree more implicitly and derive the models on demand,
or should I simply use SVN in TBC?

Any ideas would be most welcome
Thanks
Arthur
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