Data visualization is currently a very active and vital area of
research, teaching and development. The term unites the established
field of scientific visualization and the more recent field of
information visualization. The success of data visualization is due
to the soundness of the basic idea behind it: the use of
computer-generated images to gain insight and knowledge from data
and its inherent patterns and relationships. A second premise is
the utilization of the broad bandwidth of the human sensory system
in steering and interpreting complex processes, and simulations
involving data sets from diverse scientific disciplines and large
collections of abstract data from many sources.
These concepts are extremely important and have a profound and
widespread impact on the methodology of computational science and
engineering, as well as on management and administration. The
interplay between various application areas and their specific
problem solving visualization techniques is emphasized in this
book. Reflecting the heterogeneous structure of Data Visualization,
emphasis was placed on these topics:
-Visualization Algorithms and Techniques;
-Volume Visualization;
-Information Visualization;
-Multiresolution Techniques;
-Interactive Data Exploration.
Data Visualization: The State of the Art" "presents the state of
the art in scientific and information visualization techniques by
experts in this field. It can serve as an overview for the
inquiring scientist, and as a basic foundation for developers. This
edited volume contains chapters dedicated to surveys of specific
topics, and a great deal of original work not previously published
illustrated by examples from a wealth of applications. The book
will also provide basic material for teaching the state of the art
techniques in data visualization.
Data Visualization: The State of the Art is designed to meet the
needs of practitioners and researchers in scientific and
information visualization. This book is also suitable as a
secondary text for graduate level students in computer science and
engineering.
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