Visualization (graphics)

Several terms redirect here. For other uses, seeVisualization (disambiguation).

Visualization of how a car deforms in an asymmetrical crash usingfinite element analysis

Visualization(orvisualisation(seespelling differences)), also known as Graphics Visualization, is any technique for creatingimages,diagrams,oranimationsto communicate a message. Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of humanity. from history includecave paintings,Egyptian hieroglyphs,Greekgeometry,andLeonardo da Vinci's revolutionary methods of technical drawing for engineering purposes that actively involve scientific requirements.

Visualization today has ever-expanding applications in science, education, engineering (e.g., product visualization),interactive multimedia,medicine,etc. Typical of a visualization application is the field ofcomputer graphics.The invention of computer graphics (and3D computer graphics) may be the most important development in visualization since the invention ofcentral perspectivein theRenaissanceperiod. The development ofanimationalso helped advance visualization.

Overview

ThePtolemy world map,reconstituted from Ptolemy'sGeographia(circa 150), indicating the countries of "Serica"and" Sinae "(China) at the extreme right, beyond the island of "Taprobane" (Sri Lanka,oversized) and the "Aurea Chersonesus" (Southeast Asian peninsula)

Charles Minard's information graphic ofNapoleon's march

The use of visualization to present information is not a new phenomenon. It has been used in maps, scientific drawings, and data plots for over a thousand years. Examples fromcartographyincludePtolemy's Geographia(2nd century AD), a map of China (1137 AD), andMinard's map (1861) ofNapoleon'sinvasion of Russiaa century and a half ago. Most of the concepts learned in devising these images carry over in a straightforward manner to computer visualization.Edward Tuftehas written three critically acclaimed books that explain many of these principles.

Computer graphics has from its beginning been used to study scientific problems. However, in its early days the lack of graphics power often limited its usefulness. The recent emphasis on visualization started in 1987 with the publication of Visualization in Scientific Computing, a special issue of Computer Graphics.Since then, there have been several conferences and workshops, co-sponsored by theIEEE Computer SocietyandACM SIGGRAPH,devoted to the general topic, and special areas in the field, for example volume visualization.

Most people are familiar with the digital animations produced to presentmeteorologicaldata during weather reports ontelevision,though few can distinguish between those models of reality and thesatellite photosthat are also shown on such programs. TV also offers scientific visualizations when it shows computer drawn and animated reconstructions of road or airplane accidents. Some of the most popular examples of scientific visualizations arecomputer-generated imagesthat show realspacecraftin action, out in the void far beyond Earth, or on otherplanets.Dynamic forms of visualization, such aseducational animationortimelines,have the potential to enhance learning about systems that change over time.

Apart from the distinction between interactive visualizations and animation, the most useful categorization is probably between abstract and model-based scientific visualizations. The abstract visualizations show completely conceptual constructs in 2D or 3D. These generated shapes are completely arbitrary. The model-based visualizations either place overlays of data on real or digitally constructed images of reality or make a digital construction of a real object directly from the scientific data.

Scientific visualization is usually done with specializedsoftware,though there are a few exceptions, noted below. Some of these specialized programs have been released asopen sourcesoftware, having very often its origins in universities, within an academic environment where sharing software tools and giving access to the source code is common. There are also manyproprietary softwarepackages of scientific visualization tools.

Models and frameworks for building visualizations include thedata flowmodels popularized by systems such as AVS, IRIS Explorer, andVTKtoolkit, and data state models in spreadsheet systems such as the Spreadsheet for Visualization and Spreadsheet for Images.

Applications

Scientific visualization

Simulation of a Raleigh–Taylor instability caused by two mi xingfluids

Main article:Scientific visualization

As a subject incomputer science,scientific visualizationis the use of interactive, sensory representations, typically visual, of abstract data to reinforcecognition,hypothesisbuilding, andreasoning. Scientific visualizationis the transformation, selection, or representation of data from simulations or experiments, with an implicit or explicit geometric structure, to allow the exploration, analysis, and understanding of the data. Scientific visualization focuses and emphasizes the representation of higher order data using primarily graphics and animation techniques.It is a very important part of visualization and maybe the first one, as the visualization of experiments and phenomena is as old asscienceitself. Traditional areas of scientific visualization areflow visualization,medical visualization,astrophysical visualization,andchemical visualization.There are several different techniques to visualize scientific data, withisosurface reconstructionanddirect volume renderingbeing the more common.

Data and information visualization

Main article:Data and information visualization

Further information:Infographics

Relative average utilization ofIPv4

Data visualization is a related subcategory of visualization dealing withstatistical graphicsandgeospatial data(as inthematic cartography) that is abstracted in schematic form.

Information visualization concentrates on the use of computer-supported tools to explore large amount of abstract data. The term "information visualization" was originally coined by the User Interface Research Group at Xerox PARC and includedJock Mackinlay.Practical application of information visualization in computer programs involves selecting,transforming,and representing abstract data in a form that facilitates human interaction for exploration and understanding. Important aspects of information visualization are dynamics of visual representation and the interactivity. Strong techniques enable the user to modify the visualization in real-time, thus affording unparalleled perception of patterns and structural relations in the abstract data in question.

Educational visualization

Educational visualization is using asimulationto create an image of something so it can be taught about. This is very useful when teaching about a topic that is difficult to otherwise see, for example,atomic structure,because atoms are far too small to be studied easily without expensive and difficult to use scientific equipment.

Knowledge visualization

The use of visual representations to transfer knowledge between at least two persons aims to improve the transfer ofknowledgeby usingcomputerand non-computer-based visualization methods complementarily.Thus properly designed visualization is an important part of not only data analysis but knowledge transfer process, too.Knowledge transfer may be significantly improved using hybrid designs as it enhances information density but may decrease clarity as well. For example, visualization of a 3Dscalar fieldmay be implemented using iso-surfaces for field distribution and textures for the gradient of the field.Examples of such visual formats aresketches,diagrams,images,objects, interactive visualizations, information visualization applications, and imaginary visualizations as instories.While information visualization concentrates on the use of computer-supported tools to derive new insights, knowledge visualization focuses on transferring insights and creating newknowledgeingroups.Beyond the mere transfer offacts,knowledge visualization aims to further transferinsights,experiences,attitudes,values,expectations,perspectives,opinions,andpredictionsby using various complementary visualizations. See also:picture dictionary,visual dictionary

Product visualization

Product visualizationinvolves visualization software technology for the viewing and manipulation of 3D models, technical drawing and other related documentation of manufactured components and large assemblies of products. It is a key part ofproduct lifecycle management.Product visualization software typically provides high levels of photorealism so that a product can be viewed before it is actually manufactured. This supports functions ranging from design and styling to sales and marketing.Technical visualizationis an important aspect of product development. Originallytechnical drawingswere made by hand, but with the rise of advancedcomputer graphicsthedrawing boardhas been replaced bycomputer-aided design(CAD). CAD-drawings and models have several advantages over hand-made drawings such as the possibility of3-Dmodeling,rapid prototyping,andsimulation.3D product visualization promises more interactive experiences for online shoppers, but also challenges retailers to overcome hurdles in the production of 3D content, as large-scale 3D content production can be extremely costly and time-consuming.

Visual communication

Visual communicationis thecommunicationofideasthrough the visual display ofinformation.Primarily associated withtwo dimensionalimages,it includes:Alpha numerics,art,signs,andelectronicresources. Recent research in the field has focused onweb designand graphically orientedusability.

Visual analytics

Visual analyticsfocuses on human interaction with visualization systems as part of a larger process of data analysis. Visual analytics has been defined as "the science of analytical reasoning supported by the interactive visual interface".

Its focus is on human information discourse (interaction) within massive, dynamically changing information spaces. Visual analytics research concentrates on support for perceptual and cognitive operations that enable users to detect the expected and discover the unexpected in complex information spaces.

Technologies resulting from visual analytics find their application in almost all fields, but are being driven by critical needs (and funding) in biology and national security.

Interactivity

See also:Interactive data visualizationandInteractive whiteboard

Interactive visualizationorinteractive visualisationis a branch ofgraphic visualizationincomputer sciencethat involves studying how humans interact with computers to create graphic illustrations of information and how this process can be made more efficient.

For a visualization to be considered interactive it must satisfy two criteria:

• Human input: control of some aspect of the visualrepresentationof information, or of the information being represented, must be available to a human, and
• Response time: changes made by the human must be incorporated into the visualization in a timely manner. In general, interactive visualization is considered asoft real-timetask.

One particular type of interactive visualization isvirtual reality(VR), where the visual representation of information is presented using an immersive display device such as a stereo projector (seestereoscopy). VR is also characterized by the use of a spatial metaphor, where some aspect of the information is represented in three dimensions so that humans can explore the information as if it were present (where instead it was remote), sized appropriately (where instead it was on a much smaller or larger scale than humans can sense directly), or had shape (where instead it might be completely abstract).

Another type of interactive visualization is collaborative visualization, in which multiple people interact with the same computer visualization to communicate their ideas to each other or to explore information cooperatively. Frequently, collaborative visualization is used when people are physically separated. Using several networked computers, the same visualization can be presented to each person simultaneously. The people then make annotations to the visualization as well as communicate via audio (i.e., telephone), video (i.e., a video-conference), or text (i.e.,IRC) messages.

Human control of visualization

The Programmer's Hierarchical Interactive Graphics System (PHIGS) was one of the first programmatic efforts at interactive visualization and provided an enumeration of the types of input humans provide. People can:

1. Picksome part of an existing visual representation;
2. Locatea point of interest (which may not have an existing representation);
3. Strokea path;
4. Choosean option from a list of options;
5. Valuateby inputting a number; and
6. Writeby inputting text.

All of these actions require a physical device. Input devices range from the common –keyboards,mice,graphics tablets,trackballs,andtouchpads– to the esoteric –wired gloves,boom arms,and evenomnidirectional treadmills.

These input actions can be used to control both theunique informationbeing represented or the way that the information is presented. When the information being presented is altered, the visualization is usually part of afeedback loop.For example, consider an aircraft avionics system where the pilot inputs roll, pitch, and yaw and the visualization system provides a rendering of the aircraft's new attitude. Another example would be a scientist who changes a simulation while it is running in response to a visualization of its current progress. This is calledcomputational steering.

More frequently, the representation of the information is changed rather than the information itself.

Rapid response to human input

Experiments have shown that a delay of more than 20msbetween when input is provided and a visual representation is updated is noticeable by most people.Thus it is desirable for an interactive visualization to provide arenderingbased on human input within this time frame. However, when large amounts of data must be processed to create a visualization, this becomes hard or even impossible with current technology. Thus the term "interactive visualization" is usually applied to systems that provide feedback to users within several seconds of input. The terminteractiveframerateis often used to measure how interactive a visualization is. Framerates measure the frequency with which an image (a frame) can be generated by a visualization system. A framerate of 50 frames per second (frame/s) is considered good while 0.1 frame/s would be considered poor. The use of framerates to characterize interactivity is slightly misleading however, since framerate is a measure ofbandwidthwhile humans are more sensitive tolatency.Specifically, it is possible to achieve a good framerate of 50 frame/s but if the images generated refer to changes to the visualization that a person made more than 1 second ago, it will not feel interactive to a person.

The rapid response time required for interactive visualization is a difficult constraint to meet and there are several approaches that have been explored to provide people with rapid visual feedback based on their input. Some include

1. Parallel rendering– where more than one computer or video card is used simultaneously to render an image. Multiple frames can be rendered at the same time by different computers and the results transferred over the network for display on a singlemonitor.This requires each computer to hold a copy of all the information to be rendered and increases bandwidth, but also increases latency. Also, each computer can render a different region of a single frame and send the results over a network for display. This again requires each computer to hold all of the data and can lead to a load imbalance when one computer is responsible for rendering a region of the screen with more information than other computers. Finally, each computer can render an entire frame containing a subset of the information. The resulting images plus the associateddepth buffercan then be sent across the network and merged with the images from other computers. The result is a single frame containing all the information to be rendered, even though no single computer's memory held all of the information. This is calledparallel depth compositingand is used when large amounts of information must be rendered interactively.
2. Progressive rendering– where a framerate is guaranteed by rendering some subset of the information to be presented and providing incremental (progressive) improvements to the rendering once the visualization is no longer changing.
3. Level-of-detail (LOD) rendering– where simplified representations of information are rendered to achieve a desired framerate while a person is providing input and then the full representation is used to generate a still image once the person is through manipulating the visualization. One common variant of LOD rendering issubsampling.When the information being represented is stored in atopologicallyrectangular array (as is common withdigital photos,MRI scans,andfinite differencesimulations), a lower resolution version can easily be generated by skippingnpoints for each 1 point rendered. Subsampling can also be used to accelerate rendering techniques such as volume visualization that require more than twice the computations for an image twice the size. By rendering a smaller image and thenscalingthe image to fill the requested screen space, much less time is required to render the same data.
4. Frameless rendering– where the visualization is no longer presented as a time series of images, but as a single image where different regions are updated over time.

See also

• Graphical perception
• Spatial visualization ability

Further reading

• Battiti, Roberto;Mauro Brunato (2011).Reactive Business Intelligence. From Data to Models to Insight.Trento, Italy: Reactive Search Srl.ISBN978-88-905795-0-9.
• Bederson, Benjamin B., andBen Shneiderman.The Craft of Information Visualization: Readings and Reflections,Morgan Kaufmann, 2003,ISBN1-55860-915-6.
• Cleveland, William S.(1993).Visualizing Data.
• Cleveland, William S. (1994).The Elements of Graphing Data.
• Charles D. Hansen, Chris Johnson.The Visualization Handbook,Academic Press(June 2004).
• Kravetz, Stephen A. and David Womble. ed. Introduction to Bioinformatics. Totowa, N.J. Humana Press, 2003.
• Mackinlay, Jock D.(1999).Readings in information visualization: using vision to think.Card, S. K.,Ben Shneiderman(eds.). Morgan Kaufmann Publishers Inc. pp.686.ISBN1-55860-533-9.
• Will Schroeder, Ken Martin, Bill Lorensen.The Visualization Toolkit,by August 2004.
• Spence, RobertInformation Visualization: Design for Interaction (2nd Edition),Prentice Hall, 2007,ISBN0-13-206550-9.
• Edward R. Tufte(1992). The Visual Display of Quantitative Information
• Edward R. Tufte (1990). Envisioning Information.
• Edward R. Tufte (1997). Visual Explanations: Images and Quantities, Evidence and Narrative.
• Matthew Ward, Georges Grinstein, Daniel Keim.Interactive Data Visualization: Foundations, Techniques, and Applications.(May 2010).
• Wilkinson, Leland.The Grammar of Graphics,SpringerISBN0-387-24544-8

External links

• National Institute of Standards and Technology
• Scientific Visualization Tutorials, Georgia Tech
• Scientific Visualization Studio (NASA)
• Visual-literacy.org,(e.g.Periodic Table of Visualization Methods)

Conferences

Many conferences occur where interactive visualization academic papers are presented and published.

• Amer. Soc. of Information Science and Technology (ASIS&T SIGVIS)Special Interest Group in Visualization Information and Sound
• ACM SIGCHI
• ACM SIGGRAPH
• ACM VRST
• Eurographics
• IEEE Visualization
• ACM Transactions on Graphics
• IEEE Transactions on Visualization and Computer Graphics