Donna J. Cox
Winter 1990, pp. 36-42

It is my belief that the future is going to involve increased collaboration and teamwork; Teamwork between the human and the computer, between the artist and the scientist, between academia and industry.

The History of Scientific Visualization

Visualization, simply defined as the formation of mental visual images, is best exemplified by a tribal depiction of the fertility goddess Venus von Willendorf. Created 30,000 years ago by a tribe in an effort to control fertility, the most important thing to note about this image is that the artists sought to record and make tangible optical reality. This concept became more sophisticated during the Renaissance with the works of Leonardo da Vinci, who revolutionized anatomical and biological illustration.

During the Renaissance, popular belief held that the visual study of nature could, in fact, reveal the hidden laws of nature. This prompted da Vinci and other artists to look beneath the surface of the skin and to record the anatomy in detail. This was quite a revolutionary idea at the time. Artists and scientists began working together to create books -- anatomy and botany books -- and new disciplines were thus created that are still important tools for physicians and scientists today. This philosophy -- that you visually study nature to reveal the hidden laws of nature -- was developed by Renaissance artists and scientists, and it set the stage for the scientific revolution. Galileo developed the scientific methodology of visually and objectively recording data that may lead to the formation of hypotheses, having one's peers test these hypotheses, and eventually forming a scientific theory. This is how scientists still work today.

In the fifteenth century, Johannes Gutenberg invented the movable-type printing press, which resulted in an increased flow of information and a contribution to both the Age of Enlightenment and the Renaissance. Likewise, in the industrial revolution in the last century, the invention of the camera had a tremendous impact on our culture in terms of visually communicating information in the print media and through television and resulting in the media-glutted society we have today.

Recently, the electronics revolution -- including satellite communication -- has created an increase in the flow of information at an exponential rate, culminating in our computer and supercomputer technology centers, in high-speed networks, and in the process of scientific visualization. Scientific visualization, of any form of visualization, is a way of coupling the eye-brain system to increase the flow of information to the human being from the computer.

The evolution of computer graphics is strikingly similar to the evolution of art in Northern Europe from 30,000 BC to the Renaissance -- that being the copying of optical reality to create illusions. Early history of computer graphics research resulted in synthetic images, designed using mathematics, with the absolute intent by researchers to create photodigital, realistic-looking imagery. While these researchers incorporated physics into the computer graphics algorithms, their primary goal involved the creation of images that copied optical reality and created illusions.

Communication Through Visualization

Some applications in computer graphics have gone beyond computer synthetic imagery in order to visually communicate information that he naked eye cannot see. The purpose here is to enhance visual information rather than create illusion. For example, an application used to transfer information to the human eye-brain system is exemplified by the digital image processing of faces. Digital image processing can be used to distort or merge faces, such as those produced by researchers at the University of Illinois at Chicago, who have composited animal and human faces to create interesting composites.

Another example of image processing involves the work of Nancy Burson, who organized an early Renaissance team in which she, as an artist, began working with scientists at MIT on a project to digitally composite a series of faces. Composites of faces can be weighted according to factors such as her Warhead I, 1983, where leaders of individual countries were combined and their faces weighted according to the number of nuclear-deployable warheads from each country, including Ronald Reagan (55%), Leonid Brezhnev (45%), and Margaret Thatcher (less than 1%).

Burson then developed the idea of projecting people's faces into the future, thereby creating "age machines" -- images that would determine what people might look like in future years. This turned out to be an extremely important application, particularly as it applies to locating and identifying missing children. The process of finding missing children can take many years, and the morphology of their faces can change drastically in that time. The capability to project a child's age into the future has become one of the most successful techniques for finding missing children and has had very important social impact.

This type of work has typically been compared to da Vinci's exploration of bone structure, distortion of faces, and the projection of faces into the future. In fact, Burson's work has been compared to a photograph by Harold Edgerton, in that she captures what the eye cannot see by itself.

Predicting Our Environment

Using whatever resources or technology is at hand to capture what the eye cannot see has been the basis of human innovation for centuries. We use scanning electron microscopes to enter into the strange world of mosquitoes; we peer into our own blood cells; we freeze time and warp space. From the frozen image of the crown on a milk splash to the infinitesimally small cosmic ray crater on a copper plate, to the image of a massive hole on Mars, human beings continually seek to probe the universe visually and to record every piece of visual information. We can extrapolate across great amounts of time and space in order to understand what a cosmic splash is. We probe the universe, using satellites to gather data and look back at our own planet, and then we take this data and input it into a computer to better understand it.

As we study and visually capture the hierarchical organization of living systems, we are now discovering symmetries and understanding this self-similar universe. From new computer technologies and methodologies developed within this century, we humans are discovering new ways to visually and numerically prove the universe. By using computer and numerical techniques such as fractal geometry, we see graphics imagery that echoes the dimensional self-similar universe. Now we can numerically, as well as visually, simulate reality with numerical models and use computer graphics to gain insight into these numerical models.

It must be emphasized here that this capacity to predict our environment by way of visualization techniques from modeling does not mean the creation of illusion. Early computer graphics research focused on illusionist, synthetic algorithms. Thus, when Grumman Corporation computer scientist G. Gardner modeled clouds, he admitted that he was no concerned with simulating the complete physical dynamics of cloud formations. In fact, he admitted that he had learned a lot from artists, such as that one doesn't have to model the backs of the clouds in order to render realistic-looking images. On the other hand, Figure 3, developed at the National Center for Supercomputing Applications (NCSA), was created from large systems of equations solved in a supercomputer simulation in order to model and predict the behavior of severe thunderstorms. This research by NCSA atmospheric scientist R. Wilhelmson incorporates scientific visualization so the scientist may record and study the numerical output of the supercomputer simulation.

The process through which this image was created includes billions of numbers that are turned into meaningful pictures for the purpose of gaining insight. The image is not just a pretty picture; it actually couples the brain system to the supercomputer in order to understand the numbers. In other words, the simulation goes beneath the surface of the visualization. Researchers can manipulate the numbers and further understand the universe in ways that human beings have never been able to before.

Using this system, we have an opportunity to bring together different disciplines using computer graphics, an important tool for education. We are, in essence, bringing together the left and right sides of the brain by teaming artists and scientists. Knowledge, at this time in our history, is so diversified and stratified, that it is crucial that we bring together through collaboration people with diverse talents and expertise.

Making the Invisible Visible

Artists and scientists have a common goal -- that of making the invisible visible. Many of the images resulting from collaborative scientific visualizations represent a convergence of art and science. These images are yielding some of the most beautiful, and meaningful, imagery of our time. For example, Figure 4 is a slice from the animation of a collision of two neutron starts. Yet this image represents a beautiful marriage of good science and aesthetic form. Likewise in Figure 5, the astrophysical jet, which could be a thousand light years in length, is an invisible phenomenon that has been made visible through collaborative efforts in art, science, and technology.

Another example of the marriage of art and science can be seen in Figures 6 and 7. This is the image of a mathematical, topological surface that was created in the mind's eye of a blind mathematician. Bernard Morin, who became blind at the age of 14, but was able to communicate his thoughts and visualization through mathematical formulas. Professor George Francis, a University of Illinois descriptive topologist, adapted a computer algorithm developed by a Morin graduate student, Francois Apery. Professor Francis; Ray Idaszak, an NCSA computer scientist, and I ran simulations to animate the mathematical transformation.

The cover of this issue of the "Review " is a still from the animation. It shows an abstract surface that is a shadow from a ten-dimensional space. Thus we called this the Venus Project. We used this scientific visualization of a mathematical homotopy to create a video that we called "Venus and Milo." In the process of our team efforts, the mathematician developed new visual techniques, the computer scientist developed new algorithms to render these one-sided mobius-strip surfaces, and the artist used these simulations as a sculpture machine to generate aesthetic forms.

My students and I decided to create an animation using Venus. I organized 13 graphic designers and artists, 4 computer scientists and engineers, and 1 music composition Ph.D. candidate, and through the class year we created a character animation using the topological homotopy. The setting for this character animation -- and scientific visualization -- is an art gallery. There is a Seurat painting in the background, as well as an ancient vase, which is a cross-cultural symbol for the female. We also used Andy Warhol pictures of Marilyn Monroe, who is a Venus goddess in her own right, and we included an invisible character, Milo, who is a janitor. In one frame (see cover) Milo is flanked by Marilyn, the Botticelli Renaissance Venus, and the synthetic Venus. He becomes interested in a box of chocolates, and the Venus becomes interested in him and the chocolates. She chooses the chocolates and infuses them with magical powers. They become "intelligent" and begin to fly around the room. The Venus goes through her mathematical homotopy as part of the animation, which constitutes the scientific visualization.

The class became a large Renaissance team with the end goal of producing a cross-disciplinary animation. The students from the various disciplines learned skills such as responsibility to and cooperation with their peers.


The supercomputer Venus is very similar to the Paleolithic Venus in Figure 1 from 30,000 years ago, the purpose of which was to bring greater fertility to the tribe. The difference is that the supercomputer Venus required several cultures and many people in order to realize this particular image. It is my belief that the future is going to involve increased collaboration and teamwork: teamwork between the human and the computer, between the artist and the scientist, between academia and industry. And I think this concept of teamwork is essential in terms of our teaching our students how to collaborate. Collaboration is as important as any other skill we can teach students, the next generation of researchers.