  In a stationary ergodic process, clustering is defined as the tendency of
events to appear in series of increased frequency separated by longer breaks.
Such behavior, contradicting the theoretical "unbiased behavior" with
exponential distribution of the gaps between appearances, is commonly observed
in experimental processes and often difficult to explain. In the last section
we relate one such empirical example of clustering, in the area of marine
technology. In the theoretical part of the paper we prove, using ergodic theory
and the notion of category, that clustering (even very strong) is in fact
typical for "rare events" defined as long cylinder sets in processes generated
by a finite partition of an arbitrary (infinite aperiodic) ergodic measure
preserving transformation.
