  The use of Hilbert curves to visualize massive vector of data is revisited
following previous authors. The Hilbert curve mapping preserves locality and
makes meaningful representation of the data. We call such visualization as
Hilbert plots. The combination of a Hilbert plot with its Fourier transform
allows to identify patterns in the underlying data sequence. The use of
different granularity representation also allows to identify periodic intervals
within the data. Data from different sources are presented: periodic,
aperiodic, logistic map and 1/2-Ising model. A real data example from the study
of heartbeat data is also discussed.
