Information Technology Reference
In-Depth Information
visual analytics, that the actionability of information visualization is essential and
it emphasizes the process of searching for insights instead of the notion of insights
per se
.
Researchers have identified a number of stages of the process of information
visualization, namely mapping data to visual form, designing visual structures, and
view transformations. Mapping data to visual form involves the transformations
of data tables, variable types, and metadata. Visual structures can be divided into
spatial substrate, marks, connection and enclosure, retinal properties, and temporal
coding. View transformations concern location probes, viewpoint controls, and
distortion.
The origins of information visualization involve computer graphics, scientific
visualization, information retrieval, hypertext, geographic information systems,
software visualization, multivariate analysis, citation analysis and others such as
social network analysis. A motivation for applying visualization techniques is a need
to abstract and transform a large amount of data to manageable and meaningful
proportions. Analysis of multidimensional data is one of the earliest application
areas of information visualization. For example, Alfred Inselberg demonstrated how
information visualization could turn a multivariate analysis into a 2-dimensional
pattern recognition problem using a visualization scheme called parallel coordinates
(Inselberg
1997
).
Research in visual information retrieval has made considerable contributions to
information visualization. Ben Shneiderman at the University of Maryland proposed
a well-known mantra to characterize how users interact with the visualization of a
large amount of information:
•
Overview: see overall patterns, trends
•
Zoom: see a smaller subset of the data
•
Filter: see a subset based on values
•
Detailed on demand: see values of objects when interactively selected
•
Relate: see relationships, compare values
•
History: keep track of actions and insights
•
Extract: mark and capture data
Users would start from an overview of the information space and zoom-in to the
part that seems to be of interest and call for more details. A common design question
is what options are available to attract users' attention most effectively. It is known
that our perception is attracted to something that is moving, probably due to our
ancestors' survival needs in hunting animals. However, a dashboard that is full of
blinking lights is probably not informative either. The precise meanings conveyed
by specific colors are strongly influenced by the local culture where the system
is located. For example, trends colored in green in a financial visualization would
be interpreted positively, whereas contours colored in dark blue in a geographic
information system may imply something that is under the sea level.
Mapping scientific frontiers can draw valuable insights from many exciting
exemplars of information visualization. We will see in later chapters what
constitutes the paradigmatic structure of hypertext. It is geographic configurations
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