Extracting science from surveys of our Galaxy
  Our knowledge of the Galaxy is being revolutionised 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 -- we should not
attempt to "invert" the data from the space of observables into the physical
space of the Galaxy. Currently just one class of model has the required
capability, so-called "torus models". A pilot application of torus models to
understanding the structure of the Galaxy's thin and thick discs has already
produced two significant results: a major revision of our best estimate of the
Sun'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.
