VISUALIZATION

Visualization  is a technique for creating images and pictures, diagrams, or animations to communicate  a message. Visualization through imagery has been an efficient  way to communicate both abstract and  concrete ideology  since the dawn of humanity. Examples from history include cave paintings, Greek  geometry, and Leonardo da Vinci's revolutionary methods of technical drawing for engineering.

Visualization today has ever increasing applications in science, education, engineering  interactive multimedia, medicine, etc. Typical of a visualization application is the field of  computer graphics. The invention of 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. 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 is surface 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 .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

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.  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. 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 etc.

Product visualization

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.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.

Visual communication

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

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

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.

