Visualization of Information
VISUALIZATION OF INFORMATION
Visualization is defined in the Oxford English Dictionary as "the action or fact of visualizing, the power or process of forming a mental picture or vision of something not actually present to the sight." As the old adage "a picture is worth a thousand words" goes, visualization can be defined as a method that makes the best use of a person's perceptual abilities to observe, access, and understand data and information. Generally speaking, the purpose of visualization is to provide the user with not only a visual presentation and interpretation of the data and information but also a better understanding of the phenomenon behind the data and information. A more recent and domain-specific definition of visualization is given by the following: "Visualization provides an interface between two powerful information processing systems—human mind and the modern computer. Visualization is the process of transforming data, information, and knowledge into visual form making use of human's natural visual capabilities. With effective visual interfaces we can interact with large volumes of data rapidly and effectively to discover hidden characteristics, patterns, and trends" (Gershon, Eick, and Card, 1998, p. 9).
There are many ways to approach the concept of visualization. Edward Tufte (1990) categorizes visualization into three types: pictures of numbers (e.g., statistic graphs), pictures of nouns (e.g., maps and aerial photographs), and pictures of verbs (e.g., representations of motion, process, cause and effect). Visualization through computers can be portrayed as pictures and graphs, two-dimensional and three-dimensional images, three-dimensional models and simulations, animations, video segments, and so on. Visualization has been studied by a variety of scholars and researchers from such disciplines as art history, cognitive science, computer graphics, epistemology, graphic design, image processing, linguistics, semiotics, technical communication, and visual interfaces.
History of Visualization
The use of images to represent objects from the real world has a long history. As far back as 20,000 B.C.E., humans began to draw, paint, or carve images on cave walls to record and depict aspects of their experiences. For example, the Paleolithic cave paintings found in the Remigia Cave at La Gasulla in Spain vividly illustrate a group of hunters killing a wild boar. However, the use of graphs, pictures, and drawings was not restricted to the recording and depicting of objects; visualization also became an effective means for representing abstract concepts and communicating abstract ideas. The ancient Egyptian hieroglyphics are pictures that were used as a form of visual communication. The term "ideograph" refers to a symbol that is used to represent a concept in a pictographic language. In modern Chinese, for example, there are more than fifty thousand ideographs.
Visual representation of information has been helpful in assisting humans with the description, classification, analysis, and comprehension of the natural world. Astronomy, cartography, and meteorology were some of the earliest fields to use visualization techniques. For example, the astronomical images painted in the tomb of Pharaoh Seti I in 1290 B.C.E. describe the relationship between Egyptian astronomy and mythology. The earliest map to use a latitude/longitude grid was drawn in China in 1137 to depict the travels of Da Yu (Yu the Great). In the 1920s, American mete-orologists began to use symbols and pictograms to represent such natural phenomena as hail, lighting, snow, and thunderstorms in their weather charts.
Ever since Leonardo da Vinci created perspective drawing in the 1400s, the technique has been used as the primary method for creating technical graphics communications. In the late 1700s, Gaspard Monge developed the science of descriptive geometry, which provided the foundation for three-dimensional representations using two-dimensional media. Wilhelm Röntgen's discovery of x-rays in 1895 made it possible for humans to visualize what could not be seen with the naked eyes. The discovery also revolutionized the scientific fields of medicine and chemistry because it resulted in x-ray photography and chemical crystallography, respectively.
The Semi-Automatic Ground Environment (SAGE) system was the first time that computers were used for visualizing information. The system, which was developed in the United States in the mid 1950s, used interactive computer graphics combined with radar to track, analyze, and display aircraft positions on a cathode-ray-tube monitor. In 1965, Ivan Sutherland designed Sketchpad, a minicomputer drawing system. The field of computer graphics quickly developed to produce applications such as computer-aided design (CAD), geographical mapping, and molecular modeling. With the development of more powerful computers, better software, and advanced interaction techniques, virtual reality became possible. Using this technology, it has become possible to explore information visually and interactively in real time.
A large variety of visualization techniques have been used for different applications. Some commonly used techniques of visualization include bar charts, pie charts, HiLo glyphs, XY diagrams, scatter plots, treemaps, contour plots, cone trees, fractal rooms, hyperbolic trees, and perspective walls.
Scientific Visualization Versus Information Visualization
Visualization can be divided into two areas: scientific visualization and information visualization. Scientific visualization primarily deals with data or information that describe physical or spatial objects (e.g., the human body, the earth, and molecules), and information visualization primarily visualizes data or information that is non-physical or abstract (e.g., text, hierarchy, and statistics). Both areas of visualization share the same goal of using visual representations via computers to access, explore, explain, organize, and understand the data and information.
According to I. Herman, G. Melanáon, and M. S. Marshall (2000), there are three essential differences between the two areas. First, the data or information that is visualized by scientific visualization is different from the data or information that is visualized by information visualization; the former often has an inherent geometry, but the latter does not. Second, the users of scientific visualization are different from the users of information visualization; the former are usually experts, while the latter may have different levels of expertise. Third, scientific visualization and information visualization have different computer requirements; scientific visualization demands the capability of complex computation and graphic representation, which is not always necessary with information visualization. Therefore, scientific visualization, a well-established yet relatively specialized field with a relatively small number of scientists, involves many visualization techniques, uses various software tools, and requires enormous computer resources to make data or information more accessible and comprehensible. Information visualization, one of the increasingly important subfields of Human-Computer Interaction (HCI), takes advantage of the graphical capabilities of the computer and the perceptual abilities of the user to process, interpret, and understand data and information visually.
Typical Applications of Visualization
Visualization of information has many practical applications, ranging from the visualization of simple numerical data to the visualization of complex molecular structures. Some typical applications of visualization techniques are those related to geography, software, medicine, education, information retrieval, data mining and electronic commerce.
Geographical information systems (GIS) were designed to collect, store, retrieve, manipulate, and display geographically referenced data. GIS visually helps users to gain new insights related to the data and to solve complex research, planning, and management problems. GIS software is developed all over the world, but three of the better-known products are Maptitude, GeoMedia, and MapInfo.
Software visualization uses computer graphics and animation to illustrate and present computer programs, processes, and algorithms. Software visualization systems are a way to help programmers understand their code in a more effective way, and they can also be used to help teach students how algorithms work in programming. There are many software visualization systems, ranging from Algorithm Animation to Visualization of Object-Oriented Programming.
The application of computerized imagery to the field of medicine has resulted in medical imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), nuclear medicine imaging (NMI), and ultrasonography. These techniques visually magnify the subtle aspects of the diagnostic, therapeutic, and healing process of patients, thus allowing the members of the clinical staff (e.g., doctors, nurses, students, technicians, and managers) to handle medical data and information in a more intuitive and effective manner. Many medical visualization tools have been developed, but two of the more popular tools are Imaging Application Platform (IAP) and Medical Imaging Software Developer's Kit (SDK).
Visualization in education helps students using images to represent and comprehend concepts and ideas, reinforce understanding, develop critical thinking, and integrate new knowledge. Visualization is helpful for teaching and learning in language arts, mathematics, medicine, social studies, science, engineering, and so on. Visualization has been used as a helpful means in some new teaching paradigms, such as web-based courses, interactive classrooms, and distributed learning. Popular software of visual learning and teaching include a.d.A.M, ClassWise, and Inspiration.
Interactive two-dimensional or three-dimensional visualization techniques can enhance the information retrieval process by providing effective visual interfaces for users to use in navigating and manipulating large amounts of textual information. Visualization techniques also help the user to identify the relationships between documents and to refine the search results until relevant information is located. Two examples of software that are used for visualization in information retrieval are Visual Thesaurus and DRLINK (Document Retrieval using LINguistic Knowledge). Visual Thesaurus presents an animated visual display of semantic relationships between words. DR-LINK is an online search service that uses natural language queries to search a text database, facilitates information retrieval with various features, and outputs the results in different ways, including bar charts and graphs.
Data mining is the analysis of data for underlying relationships, patterns, and trends that have not previously been discovered. Visualization is used in data mining to provide visual interfaces during the data analysis process, visual manipulation of the data representation, and visual presentation of the mined data for a better understanding. Some examples of data mining visualization software are Spotfire, DEVise, and WinViz.
Visualization of marketing and advertising data in market analysis provides executives, managers, and researchers with a new way to query and explore the vast amounts of customer, product, and market data that are generated by customer relationship management. For the customers of electronic commerce, visualization can be used to make it easier for them to comparison shop through interactive visual interfaces. Cult3D, ecBuilder, and Webstores 2000 are three of the companies that develop software for use with electronic commerce.
Future Trends in Visualization
With the advancement of science and technology, visualization technologies will bring people new ways to view, analyze, and interact with data and information. Several trends in visualization provide a glimpse of its future potential.
First, new technologies are being developed for new applications. For example, virtual reality as a visualization tool can help build a simpler user interface that allows users to interact directly with data in a virtual environment (e.g., CAVE—a multiperson, room-sized, high-resolution, three-dimensional video and audio environment that allows the user to control visualization parameters). Object-oriented visualization environments can be built by visual programming with functional objects (e.g., interfaces and classes are shown in different colors). In addition, animation allows the viewing of discrete images in rapid succession for studying data that vary over time.
Second, the cost of visualization technologies is decreasing dramatically. As a result, more inexpensive, standardized software and hardware for information visualization will become available and affordable.
Third, there will be more collaboration among the producers and users of visualization products. For example, collaborative visualization will enable users to share data and information visualization processes via computer-supported cooperative work using collaborative technologies, such as Habanero, Microsoft NetMeeting, and Tango. In addition, the emerging visualization libraries created by corporate and academic research groups will provide a consistent cross-platform environment for the development of graphic products.
Fourth, more attention is being given to education for visualization. Both professional and academic communities are developing guidelines and teaching materials for visualization curricula and courses. These developments include books, videos, and websites.
Finally, universally recognized visual metaphors and conventions for structuring data and information in multiple dimensions will be developed.
Visualization, as a human perceptive ability and cognitive process, has existed throughout history, and it has evolved as humans have evolved. Visualization of information via computer technology has had an enormous effect on human society even though is has only a very short history. As society and technology advance into the future, the human quest into the nature of visualization and the visualization of information will lead to a better understanding of the relationships between information, visualization, technology, human cognition, and the natural world.
Brown, Judith R.; Earnshaw, Rae; Jern, Mikael; and Vince, John. (1995). Visualization: Using Computer Graphics to Explore Data and Present Information. New York: Wiley.
Card, Stuart K.; MacKinlay, Jock D.; and Shneiderman, Ben, eds. (1999). Readings in Information Visualization: Using Vision to Think. San Francisco: Morgan Kaufmann.
Dong, Wei, and Gibson, Kathleen. (1998). Computer Visualization: An Integrated Approach for Interior Design and Architecture. New York: McGraw-Hill.
Friedhoff, Richard M., and Benzon, William. (1989). Visualization: The Second Computer Revolution. New York: Abrams.
Gershon, Naham; Eick, Stephen G.; and Card, Stuart. (1998). "Information Visualization." Interactions 5(2):9-15.
Herman, I.; Melançon, G.; and Marshall, M. S. (2000). "Graph Visualization and Navigation in Information Visualization." <http://www.cwi.nl/InfoVisu/Survey/StarGraphVisuInInfoVis.html#38950>.
Robin, Harry. (1992). The Scientific Image: From Cave to Computer. New York: Abrams.
Tufte, Edward R. (1990). Envisioning Information. Cheshire, CT: Graphics Press.
Ware, Colin. (2000). Information Visualization: Perception for Design. San Francisco, CA: Morgan Kauf-mann.