A time-series is typically a

vector (

array)
of discrete data samples in which each sample is
comprised of a

time-stamp and a

value.
Each

time-stamp
is separated by a constant value typically called the

sampling interval, or

period
and each value is

rounded
or

truncated to the nearest value that can be represented
digitally. (See also:

sampling rate)

There are a wide variety of uses for time-series data, mostly involving digital signal processing
where a signal
is any physical quantity that changes with time.

Because digital signal processing deals with
discrete time-series data, it is possible for the original
signal to have variations which are not described by a
simple discrete value.
Therefore, sometimes time-series data may come
in the form of start,
high,
low,
and end representing the starting value,
the highest value,
lowest value,
and ending value respectively.
An example of this is daily end-of-day stock data which has
an open, high, low, and close value for the whole day.