  Temporal graphs represent binary relationships that change along time. They
can model the dynamism of, for example, social and communication networks.
Temporal graphs are defined as sets of contacts that are edges tagged with the
temporal intervals when they are active. This work explores the use of the
Compressed Suffix Array (CSA), a well-known compact and self-indexed data
structure in the area of text indexing, to represent large temporal graphs. The
new structure, called Temporal Graph CSA (TGCSA), is experimentally compared
with the most competitive compact data structures in the state-of-the-art,
namely, EDGELOG and CET. The experimental results show that TGCSA obtains a
good space-time trade-off. It uses a reasonable space and is efficient for
solving complex temporal queries. Furthermore, TGCSA has wider expressive
capabilities than EDGELOG and CET, because it is able to represent temporal
graphs where contacts on an edge can temporally overlap.
