  A $\textit{resolving set}$ $R$ in a graph $G$ is a set of vertices such that
every vertex of $G$ is uniquely identified by its distances to the vertices of
$R$. Introduced in the 1970s, this concept has been since then extensively
studied from both combinatorial and algorithmic point of view. We propose a
generalization of the concept of resolving sets to temporal graphs, i.e.,
graphs with edge sets that change over discrete time-steps. In this setting,
the $\textit{temporal distance}$ from $u$ to $v$ is the earliest possible
time-step at which a journey with strictly increasing time-steps on edges
leaving $u$ reaches $v$, i.e., the first time-step at which $v$ could receive a
message broadcast from $u$. A $\textit{temporal resolving set}$ of a temporal
graph $\mathcal{G}$ is a subset $R$ of its vertices such that every vertex of
$\mathcal{G}$ is uniquely identified by its temporal distances from vertices of
$R$.
  We study the problem of finding a minimum-size temporal resolving set, and
show that it is NP-complete even on very restricted graph classes and with
strong constraints on the time-steps: temporal complete graphs where every edge
appears in either time-step 1 or 2, temporal trees where every edge appears in
at most two consecutive time-steps, and even temporal subdivided stars where
every edge appears in at most two (not necessarily consecutive) time-steps. On
the other hand, we give polynomial-time algorithms for temporal paths and
temporal stars where every edge appears in exactly one time-step, and give a
combinatorial analysis and algorithms for several temporal graph classes where
the edges appear in periodic time-steps.
