Networks as scaffolds of complex systems are intrinsically dynamic: They grow and shrink, split and merge, as well as there are processes taking place on them like spreading phenomena. As long as the time scale of the change of the network is much slower than that of the processes a static network picture is adequate. When these scales get closer to each other, a different, dynamic approach is necessary. There is a class of networks, in which the connections between the nodes are only temporarily present —these are the temporal networks. Examples are communication networks, networks based on proximity or the networks of financial transactions. Here we briefly review the characteristics of such temporal networks with special emphasis on the motifs, i.e., small, typical spatio-temporal units. We also discuss the effect of time distributions of events on spreading in temporal networks.