While most of the visualization techniques discussed thus far focus on the
display of data values and their attributes, another important application of
visualization is the conveying of relational information, e.g., how data items
or records are related to each other. These interrelationships can take many
• part/subpart, parent/child, or other hierarchical relation; • connectedness, such as cities connected by roads or computers connected by networks;
• derived from, as in a sequence of steps or stages; • shared classiﬁcation; • similarities in values; • similarities in attributes (e.g., spatial, temporal). Relationships can be simple or complex: unidirectional or bi-directional,
nonweighted or weighted, certain or uncertain. Indeed, the relationships may
provide more and richer information than that contained in the data records.
Applications for visualizing relational information are equally diverse, from
categorizing biological species, to exploring document archives, to studying
a terrorist network.