Ahlberg and Wistrand [5] have pointed out that successful visualization environments do not
depend on one single powerful visualization, but rather on an assortment of visualizations appropriate for
various tasks and data types. The use of different visualization techniques allows for representation of
data from different points of view. Some of these views, depending on data characteristics or structure will
provide a better understanding of the data than others. One such option of great promise, iconographic
visualization, but currently it is not well integrated with other visualization techniques. The integration of the
iconographic technique with other visualizations could be a key point in the use of this technique
in exploring multidimensional data sets trying to discover hidden relations.
Grinstein et. al. [18] has pointed out the benefits of integrating the iconographic technique with
systems for knowledge discovery. Up to now however no system has been developed providing such
facilities. The idea of that integration is to use the iconographic visualization as a medium to identify visual clues
that could be used as starting points for further exploration by, for example, a knowledge discovery
system. The use of the iconographic technique in identifying possible points for further exploration has not
been exploited to its full potential. Other visualization or analysis techniques could take advantage of the
iconographic technique's capacity for creating global visual representations of data sets. Its capacity of
producing displays that stimulate spontaneous perceptions of data structures, particularly of coherent data,
could also be used for helping users in the process of identifying regions for further exploration. Its
application to non-coherent databases is also promising, but more problematic as discussed next. The
integration of the iconographic technique with analysis tools or other visualizations techniques might
provide mechanisms for dealing with some of the problems faced with the application to non-coherent
databases.