- Introduction to Visualization
- Data
- User and Tasks
- Mapping
- Representation
- Interaction Issues
- Concepts of the Visualization Process
- Systems and Tools
Theme 1: Introduction to Visualization
This theme introduces students to "computer generated visualization meant to be viewed by a human", defines the term and explains its history. Some significant examples of visualization are used to motivate students for the importance of knowledge on this topic.
(1.1) History
Visualization has its ancestry in pictorial representations dating back to the origins of man. Pictographs, for whatever reasons, are human generated images. Through the centuries, we have had human generated imagery of the sections of the world for travel and warfare; imagery of plans for architectural and novel devices (church designs, Da Vinci’s airplanes, the printing machine); images to enhance stories; images of crop rotations; and more. In this century we have been able to use the computer to generate images supporting many of our modern endeavors. Computer generated data visualizations appeared in the late 40’s when tables became much too large for a human to comprehend and manage. These visualizations, then called plots, were followed by the growth of computer graphics and systems that permitted the rapid, often interactive, generation of scientific data sets. Through a strong government financial support scientific visualization prospered specifically after the mid ´80s. A key event for the growth of scientific visualization was the appearance of a report based on an NSF sponsored workshop. [McCormick, B.H., DeFanti, T.A., and Brown M.D. (eds), 1987, Visualization in Scientific Computing. Computer Graphics21(6)]
The focus in scientific visualization was on scientific data and modeling. The statistical community in the 60s and later also began using visualization to support its data exploration. In 1993, the appearance of a paper on the "information visualizer" (CACM, April 1993, Robertson et al.) was ground braking for a series of new developments in information visualization. Today we are presented with a broader context within which data visualization fits. It encompasses scientific visualization, information visualization, database visualization, software visualization and all the domain related visualizations including biomedical and geospatial visualizations.
(1.2) Definitions
The term "to visualize" in a general context [see The Oxford English Dictionary, 1989] means "to form a mental vision, image, or picture of (something not visible or present to sight, or of an abstraction); to make visible to the mind or imagination". In our context visualization means "a computer generated image or collection of images, possibly ordered, using a computer representation of data as its primary source and a human as its primary target." In [MCC87] scientific visualization has been defined as "Visualization is a method of computing. It transforms the symbolic into the geometric, enabling researchers to observe their simulations and computations. Visualization offers a method for seeing the unseen. It enriches the process of scientific discovery and fosters profound and unexpected insights. In many fields it is already revolutionizing the way scientists do science." [FOL94] describe the process of visualization as "the binding (or mapping) of data to a representation that can be perceived. The types of binding could be visual, auditory, tactile, etc. or a combination of these." "Topic" visualizations are in general subtopics of visualization, such as software visualization. Some of the topic visualizations are also seen as certain view points at the whole field of visualization by their experts, e.g. scientific visualization has been explained as the scientific approach to creating useful visualizations; because each visualization process uses data of some sort as its primary source, data visualization has been used as the most general term for visualizations; finally information visualization is the preferred term for many in the field to express the visual representation of any kind of information. Each of these "topic" visualizations can also be defined in a narrower sense, e.g. scientific visualization as "visualization of scientific computing". Visualization reaches out to other related fields, such as computer graphics, human-computer-interaction (HCI), perception. It is important to keep clear similarities as well as borders between such related fields. Several terms need to be well defined in order to be clear on the issues concerning visualization, foremost the terms visualization, individual "topic" visualizations, and data. Additionally, the expectations of related disciplines or subdisciplines and their relationship to visualization should be clarified here.
(1.2.1) Definitions of visualization
Visualization means "a computer generated image or collection of images, possibly ordered, using a computer representation of data as its primary source and a human as its primary target." Similarly this has been expressed by [FOL94] "A useful definition of visualization might be the binding (or mapping) of data to a representation that can be perceived. The types of binding could be visual, auditory, tactile, etc. or a combination of these." The term "to visualize" in a general context [see The Oxford English Dictionary, 1989] means "to form a mental vision, image, or picture of (something not visible or present to sight, or of an abstraction); to make visible to the mind or imagination". In the context of scientific visualization this term has been defined as "Visualization is a method of computing. It transforms the symbolic into the geometric, enabling researchers to observe their simulations and computations. Visualization offers a method for seeing the unseen. It enriches the process of scientific discovery and fosters profound and unexpected insights. In many fields it is already revolutionizing the way scientists do science." [MCC87] Seven years later, Gershon expanded this definition to "Visualization is more than a method of computing. Visualization is the process of transforming information into a visual form, enabling users to observe the information. The resulting visual display enables the scientist or engineer to perceive visually features which are hidden in the data but nevertheless are needed for data exploration and analysis." [GER94]
(1.2.2)
Data means "data generated from mathematical models or computations and from human and machine collection (e.g., sensors or point of sale systems)"
(1.2.3)
We distinguish between computer representation of data (one or more internal representations of data) and the (computer generated) visual representation of data.
(1.2.4)
"Topic" visualizations are in general subtopics of visualization. Some of the topic visualizations are also seen as certain view points at the whole field of visualization by their experts. E.g. scientific visualization has been explained as the scientific approach to creating useful visualizations; because each visualization process uses data of some sort as its primary source, data visualization has been used to encompass all topic visualizations; finally information visualization is the preferred term for many in the field to mean visualization as ..The following topic visualizations have reached a stage of maturity:
(1.2.5)
show the difference to other , related, disciplines.(1.3) Sample Applications
Examples of the power of visualization to gain new insights into scientific data, to understand complex concepts, or to aid in the quest for information are plentiful. In this section students "see" what visualization is about. Examples to recommend vary from application fields such as Geophysics, e.g. "The Visualization of a Storm", to Sociology and Politics, e.g. the visualization of census data; from Biochemistry. e.g. the visualization of DNA, to Information Technology, e.g. the visualization of the web.
(1.3.1) Geophysics
e.g. "The Visualization of a Storm"
(1.3.2) Biochemistry
e.g. the visualization of DNA, molecules, or crystals
(1.3.3) Engineering and Physics
e.g. the visualization of a helicopter turbine, of a wind tunnel, of the Big Bang, of Finite Elements Analysis computations
(1.3.4) Sociology and Politics
e.g. the visualization of census data, of vote distributions or the spread of aids
(1.3.5) Mathematics
e.g. the visualization of klein knots or of splines
(1.3.6) Information Technology
e.g. the visualization of the web, the visualization of retrieved documents from a query
(1.4) Impact of Future Technology Future technology
such as future storage systems, display technology, or communication systems, will have a strong impact on visualization by making it an integral part of even more application areas. Knowledge about limitations of such technology and specifically of the human capacity will be important to convey to the students.