  Graphs offer a generic abstraction for modeling entities, and the
interactions and relationships between them. Most real world graphs, such as
social and cooperation networks evolve over time, and exploring their evolution
may reveal important information. In this paper, we present TempoGRAPHer, a
system for visualizing and analyzing the evolution of a temporal attributed
graph. TempoGRAPHer supports both temporal and attribute aggregation. It also
allows graph exploration by identifying periods of significant growth,
shrinkage, or stability. Temporal exploration is supported by two complementary
strategies, namely skyline and interaction-based exploration. Skyline-based
exploration provides insights on the overall trends in the evolution, while
interaction-based exploration offers a closer look at specific parts of the
graph evolution history where significant changes appeared. We showcase the
usefulness of TempoGRAPHer in understanding graph evolution by presenting a
detailed scenario that explores the evolution of a contact network between
primary school students.
