This is shorthand notation for a "differential" of the mean and variance parameters. The longhand version goes:
This indicates a uniform probability with respect to $\mu$. A more familiar notation is:
It comes from the "proper" derivation of a PDF from a CDF.
EDIT: I initially wrote this answer in a hasty fashion, and so had a bit of unclear notation myself. In my example, I only had a 1-dimension variable $\mu_1$, and all the above relate to a 1-dimensional random variable. I think the statistical physics literature ("maxent" people) uses this notation (but not entirely sure) - Edwin Jaynes, Larry Bretthorst, Stephen Gull, and others. I've never seen it explained in any more detail than what I have given.
And second is that $I$ stands for "prior information", not an identity matrix. This is just a good habit to express $I$ explicitly as part of your assumptions - so that you don't forget that 1) they are there, and 2) you answer depends on the prior information just as much it depends on the data.