Many complex driven nonequilibrium systems are effectively
described by a superposition of several statistics on different time
scales, in short a `superstatistics'. Superstatistical techniques have
been successfully applied to a variety of complex systems, for example
turbulence (Lagrangian, Eulerian, environmental), hydroclimatic
fluctuations, pattern formation, mathematical finance, traffic delay
statistics, random matrix theory, networks, scattering processes in
high energy physics, as well as medical and biological applications. In
this talk I will first give a general overview of this concept and its
recent applications. I will then explain how to extract the relevant
superstatistical parameters out of a given experimentally measured time
series. Finally I might comment on superstatistical methods for optical
lattices.