The document provides an overview of scientific visualization, emphasizing its role in transforming complex data into visual forms for better understanding and analysis. It explores various visualization techniques and classifications, highlighting the importance of color coding and the evolution of volume rendering methods. Additionally, it discusses the impact of advancements in technology on the field and the ongoing development of visualization tools.

1. SCIENTIFIC VISUALIZATION DOWN TO BASICS
Emiliano Martínez Rivera
Multimedia Creation, Design and Engineering Master 2011
BES La Salle, Universitat Ramon Llull - Barcelona, Spain
ABSTRACT
"A useful definition of visualization might be the
Computers help us handle and process tons of information binding (or mapping) of data to a representation that can be
data. Most of the time all this data is so dense, it’s almost perceived. The types of binding could be visual, auditory,
impossible to understand from just looking at a bunch of tactile, etc. or a combination of these." [5]
numbers. Some of the data could be analyzed by computers,
but most of the time there must be somebody, a real thinking "Visualization is more than a method of computing.
person, who shall interpret the data and take conclusions Visualization is the process of transforming information into
from it to make decisions, analyze. Scientific Visualization a visual form, enabling users to observe the information.
is about converting numbers into a representation of reality, The resulting visual display enables the scientist or engineer
something more graphic so that a human being can to perceive visually features which are hidden in the data but
understand and/or communicate. nevertheless are needed for data exploration and analysis."
[6]
Index Terms— Computer Science, Computer Graphics,
Infographics, Visualization, Scientific Modeling, Shape, 1.2. Synthesis of Definitions
Art, Animation, Engineering drawings, Virtual Reality,
Image Processing [1] “Mapping from computer representations to perceptual
(visual) representations, choosing encoding techniques to
1. INTRODUCTION maximize human understanding and communication” [2]
The present paper aims to describe the Scientific 1.3. Scientific Visualization Goals
Visualization in clear terms so that any reader, no matter the
knowledge level, can understand.  exploration/exploitation of data and information
 enhancing understanding of concepts and processes
1.1. Example Definitions [2]  gaining new (unexpected, profound) insights
 making invisible visible
"Visualization is a method of computing. It transforms  effective presentation of significant features
the symbolic into the geometric, enabling researchers to  quality control of simulations, measurements
observe their simulations and computations. Visualization
 increasing scientific productivity
offers a method for seeing the unseen. It enriches the
 medium of communication/collaboration
process of scientific discovery and fosters profound and
unexpected insights. In many fields it is already
1.4. Adjacent Disciplines
revolutionizing the way scientists do science." [3]
Following is a general comparison of Visualization (V) with
"Scientific visualization is a new, exciting field of
some adjacent disciplines to better understand the
computational science spurred on in large measure by the
differences:
rapid growth in computer technology, particular in graphics
workstation hardware and computer graphics software.
 Computer Graphics (CG)
[Visualization tools] are beginning to impact our daily lives
through usage in the arts, particularly film animation, and Efficiency of algorithms versus effectiveness of use.
they hold great promise for scientific research and
education. When computer graphics is applied to scientific  Computer Vision (CV)
data for purposes of gaining insight, testing hypothesis, and Mapping from pictures to abstract description versus
general elucidation, we speak of scientific visualization." [4] mapping from abstract description to pictures.

2.  Image Processing (IP) => NSF Committee to solve problems
Mapping from data domain to data domain versus
mapping from data domain to picture domain Committee on "Graphics, Image Processing, and
Workstations" (1986)
 (Visual) Perception (VP)  sponsored by NSF / Division of Advanced Scientific
General and scientific explanation of human abilities Computing
and limitations versus goal oriented use of visual
perception in complex information presentation. Goal of committee
 recommendations to HW/SW builders to improve
 Art and Design (AD) scientific productivity
Aesthetics and style versus expressiveness and
effectiveness Result of committee
 recommendations to research communities to develop
1.5. History new concepts/techniques for "Visualization in Scientific
Computing (ViSC)"
One of the earliest examples of three-dimensional scientific
visualization was Maxwell's thermodynamic surface, Solidifying goals
sculpted in clay in 1874 by James Clerk Maxwell.[7]  workshop on "Visualization in Scientific Computing"
 sponsors: e.g. NSF and NASA
Key Publication: [3]
2. COMMON QUESTIONS AND CONCERNS
The discussion is focused on the following questions:
1. What is the improvement in the understanding of the
data as compared to the situation without visualization?
2. Which visualization techniques are suitable for one's
data? Are direct volume rendering techniques to be
preferred over surface rendering techniques?
3. Can current techniques, like streamline and particle
advection methods, be used to appropriately outline the
known visual phenomena in the system?
This prefigured modern scientific visualization
techniques which use computer graphics.[8] The success of visualization not only depends on the
results which it produces, but also depends on the
Notable early two-dimensional examples include the environment in which it has to be done. This environment is
flow map of Napoleon’s March on Moscow produced by determined by the available hardware, like graphical
Charles Joseph Minard in 1869;[9] the “coxcombs” used by workstations, disk space, color printers, video editing
Florence Nightingale in 1857 as part of a campaign to hardware, and network bandwidth, and by the visualization
improve sanitary conditions in the British army;[9] and the software. For example, the graphical hardware imposes
dot map used by John Snow in 1855 to visualize the Broad constraints on interactive speed of visualization and on the
Street cholera outbreak.[9] size of the data sets which can be handled. Many different
problems encountered with visualization software must be
Need and opportunity taken into account. The user interface, programming model,
 increased data rates from data input, data output, data manipulation facilities, and
o measuring devices: e.g. space missions, other related items are all important. The way in which these
medical instruments ("fire hose") items are implemented determines the convenience and
o scientific computing: e.g. national effectiveness of the use of the software package as seen by
supercomputer centers the scientist. Furthermore, whether software supports
 mature and cheap technology: powerful graphical distributive processing and computational steering must be
workstations, color, sufficient memory and storage taken into account. [10]

3. 3. CLASSIFICATION OF TECHNIQUES 5.1.2. Isosurfaces
Classification of visualization techniques is often based on This technique produces surfaces in the domain of the scalar
the dimension of the domain of the quantity that is quantity on which the scalar quantity has the same value, the
visualized, i.e. the number of independent variables of the so-called isosurface value. The surfaces can be colored
domain on which the quantity acts, and on the type of the according to the isosurface value or they can be colored
quantity, i.e. scalar, vector, or tensor. according to another scalar field using the texture technique.
The latter case allows for the search for correlation between
Visualization techniques can also be divided into different scalar quantities.
surface rendering techniques, and (direct) volume rendering
techniques. Surface rendering is an indirect geometry based 5.1.3. Cutting planes
technique which is used to visualize structures in 3D scalar
or vector fields by converting these structures into surface This technique makes it possible to view scalar data on a
representations first and then using conventional computer cross-section of the data volume with a cutting plane. One
graphics techniques to render these surfaces. Direct volume defines a regular, Cartesian grid on the plane and the data
rendering is a technique for the visualization of 3D scalar values on this grid are found by interpolation of the original
data sets without a conversion to surface representations. data.
5.1.4. Orthogonal slicers
4. COLOR CODING
It often occurs that one wants to focus on the influence of
Colors and light are essential to visualization. Most only two independent variables (i.e. coordinates). Thus, the
visualization techniques contain a step in which data values other independent variables are kept constant. This is what
are mapped to colors to make the range of the data visible. the orthogonal slicer method does. For example, if the data
The interpretation of results produced by these visualization is defined in spherical coordinates and one wants to focus on
techniques depends crucially on the mapping of data to the angular dependences for a specific radius, the orthogonal
colors because the human eye is more sensitive to some slicer method constructs the corresponding sphere. No
parts of the visible spectrum of light than to other parts and interpolation is used since the original grid with the
the brain may interpret different color patterns differently. corresponding data is inherited.
There exist quite a few color coding systems like the known
RGB, CMY, and HSV systems. 5.1.5. Vector glyphs
This technique uses needle or arrow glyphs to represent
5. VISUALIZATION TECHNIQUES AND METHODS vectors at each data point. The direction of the glyph
corresponds to the direction of the vector and its magnitude
This chapter introduces the visualization techniques and corresponds to the magnitude of the vector. The glyphs can
methods. The focus is on 3D scalar and vector techniques, be colored according to a scalar field.
because often data consists of 3D scalar and vector fields.
5.1.6. Streamlines, streaklines, and particle advection
5.1. Surface rendering techniques
This is a set of methods for outlining the topology, i.e. the
This section briefly describes a general set of 3D scalar and field lines, of a vector field. Generally, one takes a set of
vector surface rendering techniques. The first four starting points, finds the vectors at these points by
descriptions deal with scalar field techniques and the other interpolation, if necessary, and integrates the points along
two with vector field techniques. the direction of the vector. At the new positions the vector
values are found by interpolation and one integrates again.
5.1.1. Scalar glyphs
The difference between streamlines and streaklines is that
Scalar glyphs is a technique which puts a sphere or a the streamlines technique considers the vector field to be
diamond on every data point. The scale of the sphere or static whereas the streaklines technique considers the vector
diamond is determined by the data value. The scalar glyphs field to be time dependent. Hence, the streakline technique
may be colored according to the same scalar field or interpolates not only in the spatial direction, but also in the
according to another scalar field. In this way correlations time direction.
can be found.

4. 5.1.7. Textures 5.3.1. Flipbook animation
This is a technique to color arbitrary surfaces, e.g. those This is a well known technique. The generated images are
generated by the isosurface techniques, according to a 3D displayed one after the other. Its name is attached to the
scalar field. An interpolation scheme is used to determine thumbing or flipping through a series of images.
the values of the scalar field on the surface. A colormap is
used to assign the color. 5.3.2. Keyframe animation
5.2. Volume rendering techniques For this technique one only has to generate so-called
keyframes. Keyframes mark changes in the characteristics
Volume rendering techniques have been developed to of the motion. Interpolation techniques are used to generate
overcome problems of the accurate representation of a set of images between two keyframes.
surfaces in the isosurface techniques. In short, these
problems are related to making a decision for every volume 6. CONCLUSIONS
element whether or not the surface passes through it and this
can produce false positives (spurious surfaces) or false In such a rapidly evolving field, it is important to be aware
negatives (erroneous holes in surfaces), particularly in the of the latest developments, as well as those areas of ongoing
presence of small or poorly defined features. Volume research. Two important recent developments are of special
rendering does not use intermediate geometrical importance. The first has been the explosion of the internet.
representations, in contrast to surface rendering techniques. The growth of the web has created a new medium by which
It offers the possibility for displaying weak or fuzzy visualization can be presented with a high level of
surfaces. This frees one from the requirement to make a interaction.
decision whether a surface is present or not.
The second recent (and continuing) development is the
Two implementations of volume rendering are Ray casting increase in speed of PCs, as well as the reduction in cost of
and Splatting. The two methods differ in the way the RGBA high end workstations. This is bringing the world of
volume is projected onto the 2D viewing plane. Scientific Visualization to every possible user.
5.2.1. Ray casting 7. REFERENCES
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