  Many complex networked systems exhibit volatile dynamic interactions among
their vertices, whose order and persistence reverberate on the outcome of
dynamical processes taking place on them. To quantify and characterize the
similarity of the snapshots of a time-varying network -- a proxy for the
persistence,-- we present a study on the persistence of the interactions based
on a descriptor named \emph{temporality}. We use the average value of the
temporality, $\overline{\mathcal{T}}$, to assess how ``\emph{special}'' is a
given time-varying network within the configuration space of ordered sequences
of snapshots. We analyze the temporality of several empirical networks and find
that empirical sequences are much more similar than their randomized
counterparts. We study also the effects on $\overline{\mathcal{T}}$ induced by
the (time) resolution at which interactions take place.
