Editing Visualization (graphics) (section)

==Applications==

=== Scientific visualization ===
[[File:Rayleigh-Taylor instability.jpg|thumb|250px|Simulation of a Raleigh–Taylor instability caused by two mixing [[fluid]]s]]
{{main|Scientific visualization}}

As a subject in [[computer science]], [[scientific visualization]] is the use of interactive, sensory representations, typically visual, of abstract data to reinforce [[cognition]], [[hypothesis]] building, and [[reasoning]].
[[Scientific visualization]] is 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.<ref>"Scientific Visualization." sciencedaily.com. Science Daily, 2010. Retrieved from web [https://www.sciencedaily.com/articles/s/scientific_visualization.htm https://www.sciencedaily.com/articles/s/scientific_visualization.htm]. on 17 November 2011.</ref><ref>"Scientific Visualization." Scientific Computing and Imaging Institute. Scientific Computing and Imaging Institute, University of Utah, n.d. Retrieved from web [http://www.sci.utah.edu/research/visualization.html http://www.sci.utah.edu/research/visualization.html]. on 17 November 2011.</ref> It is a very important part of visualization and maybe the first one, as the visualization of experiments and phenomena is as old as [[science]] itself. Traditional areas of scientific visualization are [[flow visualization]], [[medical visualization]], [[astrophysical visualization]], and [[molecular graphics|chemical visualization]]. There are several different techniques to visualize scientific data, with [[isosurface|isosurface reconstruction]] and [[volume rendering|direct volume rendering]] being the more common.

=== Data and information visualization ===
{{main|Data and information visualization}}
{{further|Infographics}}
[[File:Carnabotnet geovideo lowres.gif|thumb|250px|Relative average utilization of [[IPv4]]]]

Data visualization is a related subcategory of visualization dealing with [[statistical graphics]] and [[geospatial data]] (as in [[thematic map|thematic cartography]]) that is abstracted in schematic form.<ref name = "MF08">[[Michael Friendly]] (2008). [https://web.archive.org/web/20180926124138/http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf "Milestones in the history of thematic cartography, statistical graphics, and data visualization"]. Project moved to http://datavis.ca/milestones/</ref>

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 included [[Jock D. Mackinlay|Jock Mackinlay]].{{Citation needed|date=January 2013}} Practical application of information visualization in computer programs involves selecting, [[data transformation|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 a [[simulation]] to 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 of [[knowledge]] by using [[computer]] and non-computer-based visualization methods complementarily.<ref>(Burkhard and Meier, 2004),</ref> Thus properly designed visualization is an important part of not only data analysis but knowledge transfer process, too.<ref>{{Cite journal|last=Opiła|first=Janusz|date=1 April 2019|title=Role of Visualization in a Knowledge Transfer Process|journal=Business Systems Research Journal|volume=10|issue=1|pages=164–179|doi=10.2478/bsrj-2019-0012|issn=1847-9375|doi-access=free}}</ref> 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 3D [[scalar field]] may be implemented using iso-surfaces for field distribution and textures for the gradient of the field.<ref>{{Cite book|last1=Opila|first1=J.|last2=Opila|first2=G.|title=2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) |chapter=Visualization of computable scalar 3D field using cubic interpolation or kernel density estimation function |date=May 2018|location=Opatija|publisher=IEEE|pages=0189–0194|doi=10.23919/MIPRO.2018.8400036|isbn=9789532330953|s2cid=49640048}}</ref> Examples of such visual formats are [[sketch (drawing)|sketch]]es, [[diagram]]s, [[image]]s, objects, interactive visualizations, information visualization applications, and imaginary visualizations as in [[narrative|stories]]. While information visualization concentrates on the use of computer-supported tools to derive new insights, knowledge visualization focuses on transferring insights and creating new [[knowledge]] in [[group (sociology)|groups]]. Beyond the mere transfer of [[fact]]s, knowledge visualization aims to further transfer [[insight]]s, [[experience]]s, [[attitude (psychology)|attitude]]s, [[value (personal and cultural)|value]]s, [[expectation (epistemic)|expectation]]s, [[perspective (cognitive)|perspective]]s, [[opinion]]s, and [[estimate]]s in different fields by using various complementary visualizations.
See also: [[picture dictionary]], [[visual dictionary]]

=== Product visualization ===
[https://superdna3dlab.com/how-better-3d-product-visualization-reduce-the-risk-of-returns/ Product visualization] involves 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 of [[product 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 visualization'' is an important aspect of product development. Originally [[technical drawing]]s were made by hand, but with the rise of advanced [[computer graphics]] the [[drawing board]] has been replaced by [[computer-aided design]] (CAD). CAD-drawings and models have several advantages over hand-made drawings such as the possibility of [[3-D computer graphics|3-D]] modeling, [[rapid prototyping]], and [[simulation]]. 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.<ref>{{Cite web|url=https://www.slideshare.net/FelixLimper/3d-workflows-in-global-ecommerce-why-your-retail-business-needs-a-3d-ar-strategy-and-how-to-efficiently-realize-it-on-a-large-scale|title=3D Workflows in Global E-Commerce|website=www.dgg3d.com|date=28 February 2020|access-date=2020-04-22}}</ref>

=== Visual communication ===
[[Visual communication]] is the [[communication]] of [[idea]]s through the visual display of [[information]]. Primarily associated with [[two dimensional]] [[image]]s, it includes: [[alphanumeric]]s, [[art]], [[information sign|sign]]s, and [[electronics|electronic]] resources. Recent research in the field has focused on [[web design]] and graphically oriented [[usability]].

=== Visual analytics ===
[[Visual analytics]] focuses 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".<ref>Thomas, J.J., and Cook, K.A. (Eds) (2005). An Illuminated Path: The Research and Development Agenda for Visual Analytics, IEEE Computer Society Press, {{ISBN|0-7695-2323-4}}</ref>

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.