  The study of collective animal behaviour must progress through a comparison
between the theoretical predictions of numerical models and data coming from
empirical observations. To this aim it is important to develop methods of
three-dimensional (3D) analysis that are at the same time informative about the
structure of the group and suitable to empirical data. In fact, empirical data
are considerably noisier than numerical data, and they are subject to several
constraints. We review here the tools of analysis used by the STARFLAG project
to characterise the 3D structure of large flocks of starlings in the field. We
show how to avoid the most common pitfalls i the quantitative analysis of 3D
animal groups, with particular attention to the problem of the bias introduced
by the border of the group. By means of practical examples, we demonstrate that
neglecting border effects gives rise to artefacts when studying the 3D
structure of a group. Moreover, we show that mathematical rigour is essential
to distinguish important biological properties from trivial geometric features
of animal groups.
