Graphics Reference
In-Depth Information
programs. Interactive statistical applications, e.g. Fowlkes (
); Fishkeller et al.
(
), and true high-resolution graphics were developed but would take a while
to enter common use.
By the end of this period significant intersections and collaborations would begin:
(a) Computer science research (sotware tools, C language, UNIX, etc.) at Bell Labo-
ratories (Becker,
) and elsewhere would combine forces with (b) Developments
in data analysis (EDA, psychometrics, etc.) and (c) Display and input technology
(pen plotters, graphic terminals, digitizer tablets, the mouse, etc.). hese develop-
ments would provide new paradigms, languages and sotware packages for express-
ing statistical ideas and implementing data graphics. In turn, they would lead to an
explosive growth in new visualization methods and techniques.
Other themes began to emerge, mostly as initial suggestions: (a) Various novel
visual representations of multivariate data (Andrews' (
) Fourier function plots,
Chernoff (
) faces, star plots, clustering and tree representations); (b) he devel-
opment of various dimension-reduction techniques (biplot (Gabriel,
), multi-
dimensional scaling, correspondence analysis), providing visualization of multidi-
mensional data in a
-D approximation; (c) Animations of a statistical process; and
(d) Perceptually based theory and experiments related to how graphic attributes and
relations might be rendered to better convey data visually.
By the close of this period, the first exemplars of modern GIS and interactive sys-
tems for
-D and
-D statistical graphics would appear. hese would set goals for
future development and extension.
1975-present: High-D, Interactive
and Dynamic Data Visualization
1.2.8
During the last quarter of the
th century data visualization blossomed into a ma-
ture, vibrant and multidisciplinary research area, as may be seen in this Handbook,
and sotware tools for a wide range of visualization methods and data types are avail-
able for every desktop computer. Yet it is hard to provide a succinct overview of the
most recent developments in data visualization because they are so varied and have
occurredatanaccelerated paceandacrossawiderrangeofdisciplines.Itisalsomore
di
cult to highlight the most significant developments which may be seen as such
in a subsequent history focusing on this recent period.
With this disclaimer, a few major themes stand out.
hedevelopmentofhighlyinteractive statistical computing systems.Initially, this
meant largely command-driven, directly programmable systems (APL, S), as op-
posed to compiled, batch processing;
Newparadigms of directmanipulation forvisual data analysis (linking, brushing
(Becker and Cleveland,
), selection, focusing, etc.);
New methods for visualizing high-dimensional data (the grand tour (Asimov,
), scatterplot matrix (Tukey and Tukey,
), parallel coordinates plot (In-
selberg,
; Wegman,
), spreadplots (Young,
a), etc.);
