Our knowledge of the Galaxy is being revolutionized by a series of photometric, spectroscopic and astrometric surveys. Already an enormous body of data is available from completed surveys, and data of ever-increasing quality and richness will accrue at least until the end of this decade. To extract science from these surveys, we need a class of models that can give probability density functions in the space of the observables of a survey a€“ we should not attempt to a€?inverta€? the data from the space of observables into the physical space of the Galaxy. Currently just one class of model has the required capability, the so-called a€?torus modelsa€?. A pilot application of torus models to understand the structure of the Galaxya€?s thin and thick discs has already produced two signi???cant results: a major revision of our best estimate of the Suna€?s velocity with respect to the local standard of rest, and a successful prediction of the way in which the vertical velocity dispersion in the disc varies with distance from the Galactic plane.
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