  Our goal is to extend information geometry to situations where statistical
modeling is not obvious. The setting is that of modeling experimental data.
Quite often the data are not of a statistical nature. Sometimes also the model
is not a statistical manifold. An example of the former is the description of
the Bose gas in the grand canonical ensemble. An example of the latter is the
modeling of quantum systems with density matrices. Conditional expectations in
the quantum context are reviewed. The border problem is discussed: through
conditioning the model point shifts to the border of the differentiable
manifold.
