  Datacentric enthusiasm is growing strong across a variety of domains. Whilst
data science asks unquestionably exciting scientific questions, we argue that
its contributions should not be extrapolated from the scientific context in
which they originate. In particular we suggest that the simple-minded idea to
the effect that data can be seen as a replacement for scientific modelling is
not tenable. By recalling some well-known examples from dynamical systems we
conclude that data science performs at its best when coupled with the subtle
art of modelling.
