VISUALIZATION

Visualization or visualisation (see spelling differences) is any technique for  creating images, diagrams, or animations to communicate a message. Visualization through  visual imagery has been an effective way to communicate both abstract and concrete ideas  since the dawn of humanity. Examples from history include cave paintings, Egyptian  hieroglyphs, Greek geometry, and Leonardo da Vinci's revolutionary methods of technical  drawing for engineering and scientific purposes.

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 of computer graphics. The invention of computer graphics (and 3D  computer graphics) may be the most important development in visualization since the  invention of central perspective in the Renaissance period. The development of animation also  helped advance visualization.

APPLICATION

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.[5][6] 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 chemical visualization. There are several different techniques to visualize scientific data,  with isosurface reconstruction and direct volume rendering being the more common.

Information visualization  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 Mackinlay.[citation needed] 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 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[edit]

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.[8] Thus properly designed visualization is an important part of not  only data analysis but knowledge transfer process, too.[9] 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.[10] Examples of  such visual formats are sketches, diagrams, images, objects, interactive visualizations,  information visualization applications, and imaginary visualizations as in 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 groups. Beyond the mere transfer of facts, knowledge visualization aims to  further transfer insights, experiences, attitudes, values, expectations, perspectives, opinions,  and predictions by using various complementary visualizations. See also: picture  dictionary, visual dictionary

Product visualization[edit]

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 drawings 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 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.[11][12]

Visual communication[edit]

Visual communication is the communication of ideas through the visual display of information.  Primarily associated with two dimensional images, it includes: alphanumerics, art, signs,  and electronic resources. Recent research in the field has focused on web design and  graphically-oriented usability.

Visual analytics[edit]

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".[13]

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.

INSIGHT

visualization is critical to data analysis. It provides a front line of attack, revealing intricate  structure in data that cannot be absorbed in any other way. We discover unimagined effects,  and we challenge imagined ones.

Data by itself, consisting of bits and bytes stored in a file on a computer hard drive, is invisible.  In order to be able to see and make any sense of data, we need to visualize it. In this chapter  I’m going to use a broader understanding of the term visualizing, that includes even pure  textual representations of data. For instance, just loading a dataset into a spreadsheet software  can be considered as data visualization. The invisible data suddenly turns into a visible ‘picture’  on our screen. Thus, the questions should not be whether journalists need to visualize data or  not, but which kind of visualization may be the most useful in which situation.  In other words: when does it makes sense to go beyond the table visualization? The short  answer is: almost always. Tables alone are definitely not sufficient to give us an overview of a  dataset. And tables alone don’t allow us to immediately identify patterns within the data. The  most common example here are geographical patterns which can only be observed after  visualizing data on a map. But there are also other kinds of patterns which we will see later in  this chapter.

Using visualization to Discover Insights

It is unrealistic to expect that data visualization tools and techniques will unleash a barrage of  ready-made stories from datasets. There are no rules, no ‘protocol’ that will guarantee us a  story. Instead, I think it makes more sense to look for ‘insights’, which can be artfully woven  into stories in the hands of a good journalist.

Every new visualization is likely to give us some insights into our data. Some of those insights  might be already known (but perhaps not yet proven) while other insights might be completely  new or even surprising to us. Some new insights might mean the beginning of a story, while  others could just be the result of errors in the data, which are most likely to be found by  visualizing the data.

APPROACH-

Two Approaches to Data Visualization —Understanding and Persuasion. ... This type  of visualization is often a collection of basic charts and graphs. The goal is to present the data in  an in-depth and unbiased way. The second type is visualization for persuasion.


VISUALIZATION Visualization or visualisation ( see spelling differences ) is any technique for creating images , diagrams , or animations to communicate a message . Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of humanity . Examples from history include cave paintings , Egyptian hieroglyphs , Greek geometry , and Leonardo da Vinci 's revolutionary methods of technical drawing for engineering and scientific purposes . 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 of computer graphics . The invention of computer graphics ( and 3D computer graphics ) may be the most important development in visualization since the invention of central perspective in the Renaissance period . The development of animation also helped advance visualization . APPLICATION 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.[5][6 ] 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 chemical visualization . There are several different techniques to visualize scientific data , with isosurface reconstruction and direct volume rendering being the more common . Information visualization 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 Mackinlay.[citation needed ] 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 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[edit ] 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.[8 ] Thus properly designed visualization is an important part of not only data analysis but knowledge transfer process , too.[9 ] 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.[10 ] Examples of such visual formats are sketches , diagrams , images , objects , interactive visualizations , information visualization applications , and imaginary visualizations as in 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 groups . Beyond the mere transfer of facts , knowledge visualization aims to further transfer insights , experiences , attitudes , values , expectations , perspectives , opinions , and predictions by using various complementary visualizations . See also : picture dictionary , visual dictionary Product visualization[edit ] 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 drawings 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 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.[11][12 ] Visual communication[edit ] Visual communication is the communication of ideas through the visual display of information . Primarily associated with two dimensional images , it includes : alphanumerics , art , signs , and electronic resources . Recent research in the field has focused on web design and graphically - oriented usability . Visual analytics[edit ] 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".[13 ] 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 . INSIGHT visualization is critical to data analysis . It provides a front line of attack , revealing intricate structure in data that can not be absorbed in any other way . We discover unimagined effects , and we challenge imagined ones . Data by itself , consisting of bits and bytes stored in a file on a computer hard drive , is invisible . In order to be able to see and make any sense of data , we need to visualize it . In this chapter I ’m going to use a broader understanding of the term visualizing , that includes even pure textual representations of data . For instance , just loading a dataset into a spreadsheet software can be considered as data visualization . The invisible data suddenly turns into a visible ‘ picture ’ on our screen . Thus , the questions should not be whether journalists need to visualize data or not , but which kind of visualization may be the most useful in which situation . In other words : when does it makes sense to go beyond the table visualization ? The short answer is : almost always . Tables alone are definitely not sufficient to give us an overview of a dataset . And tables alone do n’t allow us to immediately identify patterns within the data . The most common example here are geographical patterns which can only be observed after visualizing data on a map . But there are also other kinds of patterns which we will see later in this chapter . Using visualization to Discover Insights It is unrealistic to expect that data visualization tools and techniques will unleash a barrage of ready - made stories from datasets . There are no rules , no ‘ protocol ’ that will guarantee us a story . Instead , I think it makes more sense to look for ‘ insights ’ , which can be artfully woven into stories in the hands of a good journalist . Every new visualization is likely to give us some insights into our data . Some of those insights might be already known ( but perhaps not yet proven ) while other insights might be completely new or even surprising to us . Some new insights might mean the beginning of a story , while others could just be the result of errors in the data , which are most likely to be found by visualizing the data . APPROACH- Two Approaches to Data Visualization — Understanding and Persuasion . ... This type of visualization is often a collection of basic charts and graphs . The goal is to present the data in an in - depth and unbiased way . The second type is visualization for persuasion .