Expressiveness And Success OF THIS Visualization Computer Knowledge Essay

Visualization is a method or a transformation of data or information into images, diagrams, or animations. Concise Oxford Dictionary says that visualization means "to assume or remember as though actually seeing". Besides, in Webster's Ninth New Collegiate Dictionary, it includes defined visualization as "the work or procedure for interpreting in aesthetic conditions or of putting into aesthetic forms". [1] In another words, visualization is the communication of information using graphical representations.

There is no longer an obstacle for collecting data or information though extracting necessary ideals from gathered information has ended up being gradually more complex and complicated. Since start prior to the written terminology has formalized, we've been using pictures for communication and aesthetic imagery has been an efficient way to correspond both tangible and abstract ideas. We, humans, have sophisticated and great eyesight system which we utilize and count for everything we do on a daily basis while the velocity of analyzing word is quite limited for us by the sequential process of reading.

Purpose of Visualization

The main reason of visualization is to convey, explore and analyze information. To become more specific, visualization can be used to present massive amount information compactly from various view tips and at several levels of details. Furthermore, it helps us extract the important info which is concealed within the info. Visualization is vital to manage the modern world information of personal computers, satellites, digitized systems and etc.

Some data pieces are naturally easier to be represented visually since we have got the abilities of powerful individual vision system. Graphical representation makes easier for inspecting the data especially when everything and its relation are segregated with different colors, designs, and size. [1] As modern tools is enormously growing and with the inventions of all the pcs and their features to generate large data models, visualization is the most suited technology to draw out and study the information from collected uncooked data.

Some types of visualization comprise mapping the blogosphere, web pattern map which really is a detailed research of the existing online fads, and hierarchical composition of the internet that presents the connectivity and exactly how it is being managed. In addition, visualization offers sizeable financial advantages in today's competitive world. Computer simulation together with visualization can save product expenses and time required for production.

Types of Visualization

There're few terminologies that can be used to symbolize visualization. Scientific visualization in computer science field means the method of graphically exhibiting real or simulated data. It really is a simple process in the ground breaking realization of technological ideas and its own basic visualization techniques contain surface rendering, volume rendering, computer animation, handling algorithms and other sensory display such as sound or touch. [1]

Another phrase expressing visualization is data visualization. Data visualization is more general compared to clinical visualization as its data sources entail business, marketing and financial data which can be beyond sciences and anatomist fields. [1] Additionally, it includes statistical operations and other standard data analysis techniques.

Information visualization can be used to imagine abstract information and abstract constructions, directory data on pcs, hypertext documents on INTERNET, etc. [1] It pulls on the intellectual history of several customs like computer design, human computer interaction and statistical images.

Visualization can be grouped based on framework where data exists. Based on the data models, the techniques of visualization are differed. Scientific visualization methods are used when data exists up to three spatial coordinates and time sizing whereas information visualization is good for data in higher dimensional or abstract places. Scientific visualization and information visualization overlap the other person and they are allied domains. [1] The relationship of three different visualizations can be found as in figure 1.

Figure 1: Types of Visualization

Visualization Process

Figure 2 illustrates the steps of visualization process. [2] The very first step of making visualization is approximately analyzing the info to be visualized. It's important to find out whether data from a repository, a file or some source, simple or intricate, can be organized and permits easy modification to match its visualization. The designer needs to take note of the demonstration of the visualization results and the information the users desire to remove from the gigantic data set. Organic data will be then changed into symbolic representations.

Secondly, the info principles themselves or the info characteristics are mapped as graphical things, such as patterns, lines, color, position and size. The last element of visualization process is making of graphic items by the computer onto the display and era of visualization for the user's interpretation.

Figure 2: Visualization Process from HIGHER LEVEL View

Visualizing Information

One of the essential questions in information visualization is how to spell it out expressiveness and effectiveness, the two mathematical steps of visualization, which can be applied at all stages of visualization process. Besides when visualizing, there're some important variables to consider such as visualization and icons, visual features and the eight aesthetic variables.

Expressiveness and Success of the Visualization

Jock D. Mackinlay, an American visualization expert, claims "a visualization is expressive if the visualization encodes all relevant information in support of that information". [3] That denotes the person could see all information he/ she needs to examine with no interruptions. Therefore, expressiveness measures the focus of information. Perfect visualization means with ideal expressiveness which is tough to attain in reality. Expressing too much information will lead to interference of interpreting essential information and expressing less information will miss out important datasets need to be visualized. Effectiveness means that all information is presented clearly and quickly in an inexpensive manner. [3] Hence performance measures a precise cost of information understanding.

Beshers & Feiner, the experts, adapt these two measures and express it as potential expressiveness and potential effectiveness. [3] A visualization is probably expressive, if it has the potential and under an individual control to display all essential information as time passes. It is probably effective, if the information provided is sufficiently clear as time passes.

Visualization and Symbols

In visualization, icons create a wide range of new prospects for visual effects. Symbols have been used to hook up with many intentions and they play as valuable assignments in information visualization. Visual objects are visual symbols that are elements of visualization like arrows, labels, dots and etc. To find relations or habits of visualization, Cleveland state governments that we now have two major steps. [4] The first step is a mapping between graphic symbols and the symbolized data. Lastly finding habits on the display that imply the habits in the info.

Graphic Features

Graphics are represented in three or even more dimensions. Each and every point of any graphic is construed as a relation between two positions x and y with a third variable value z. Images can be analyzed in three main steps. [2] First is to perceive groups of things pre-attentively, accompanied by characterizing those categories cognitively. The final step is to look at special cases that are out of the group.

The Eight Visual Variables

To represent different facets of the same information, choosing aesthetic variables is vital and make a difference the conception and understanding of the presented information. Thus, it is essential to understand visual primitives and their factors. The eight visible factors are as below. [2]

Position

It is the most important visual changing and changes in x, y location. In visualization, the spatial arrangement is the very first thing to be done. That is the reason why positioning has the greatest impact on the screen of information.

Shape

Shapes or marks refer to points, lines, areas, quantities, and their compositions, and they are graphic primitives that symbolize data. A couple of infinite volume of shapes plus they are being used for categorization.

Size

Size changes in area, span or amount. It influences the way of specific data representation and display.

Brightness

Brightness or luminance is good for large period and constant data. However, there is a limitation to distinguish among all those different levels of brightness.

Color

It changes corresponding to two variables, hue and saturation. It requires mapping of data ideals to individual color codes.

Orientation

Orientation changes in alignment. It can't be used for any marks. For instance, circles look the same even their orientations change. Patterns with natural single axis will be the best to apply orientation.

Texture

It is a mixture of several other visual factors including grades, color, orientation and so on.

Motion

Motion describes all visual variables change as time passes and it can have an overabundance of information.

Human Belief System

Visual notion means the capability to interpret and process information from noticeable light in the encompassing environment. Not everyone perceives data exactly the same. Different viewers differently interpret the identical visible representations.

When developing visualization, to reduce the confusion later on, the designers need to take accounts of color consumption of visual entities for appropriate measurement, quantity of distinct entities, and etc. Besides, we also need to consider the primitives that humans usually discover pre-attentively and the amount of accuracy we perceive various primitives. Subsequently, when we imagine data, it is a simple requirement to learn the limits of human perception since we need to factor in these limitations and avoid producing images with obscure or deceptive information.

Visual System

The eye is composed of many parts. [5] They obtain aesthetic images, concentrate them accurately and send communications to the mind. The primary sensory element of eye-sight assembles light dispersed from things and varieties a two dimensional function on the photoreceptors, the tiny sensory devices which act in response in the occurrence of photons creating light waves.

Information related to the external objects in the environment is captured through the visual system. Light rays from an thing enters through the outer part of the eye, known as the cornea. It can help the eye to target to make things look sharpened and clear. Then, the light rays travel towards an opening called the pupil, the dark circular circle in the middle of the colored area of the eye. The shaded eye is called the iris and the pupil is merely a opening in the iris. The iris controls the amount of light goes into the attention. Besides, your eyes also has a lens to focus the light rays. Light goes by through the lens till the back of the attention, the retina. They have millions of very small light sensitive cells sending communications to parts of the brain, the optic nerves.

Field of View

A couple of normal healthy human eye can view about 200 degrees horizontally where about 120 levels of which are distributed by both eyes and giving surge to what's known as binocular perspective. [6] It has a field of view of 135 degrees vertically. However, even as grow older, these values decrease. Both of individuals eyes sit more or less on the front of our heads which is common in victim species as it can help increase an animal's total field of view.

Angular Resolution

Angular resolution identifies the least distance of which our eye can distinguish things of the same size and shape from each other. [6] The normal set of human eyes has an angular resolution of 1 minute of arc. This means objects one degree apart from each other can be recognized. Therefore, angular quality is useful when we need to distinguish similar objects. Nevertheless, every eye differs and their angular quality varies predicated on eyesight strength, attention shape and get older.

The Blind Spot

The photoreceptor cells in our eye are being used to understand light and information being received is relayed to the brain via the optic nerve. Blind spot is the visual field where it lacks the light detecting photoreceptor skin cells on the optic disk of the retina. [6] A little part of the field of eye-sight is not regarded as there are no skin cells to discover light. Normally, with two sight, the brain interpolates the blind location based on encircling details and information from the other eyes so the blind spot wouldn't normally be recognized. However, blind location can be perceived easily with one eyes closed.

Perceptual Processing

Attention functions as a critical role in perceiving information. Belief can be pre-attentive or attentive. Usually the circulation of perceived information begins from the reduced level pre-attentive towards the high cognitive periods.

Professor Treisman says perceptions that can be performed in less than 200 to 250ms are regarded as pre-attentive. [7] Initiating random locations of the elements in screen by human eyes normally take at least 200ms. That determines attention can't be pre-focused on any particular situation and information is processed in parallel by the real human visible system. Pre-attentive belief requires its objects to possess a distinctive feature, such as color and size.

For attentive conception, it uses short term memory and it is selective. Attentive responsibilities convert early image effects into a well-structured objects. Attentive perception is generally slower and often implies aggregates of what's in the world.

When designing visualization, the designers should take note of pros and cons of the human visual system and provide well-suited visuals to the audiences for easy research. Thus, to be able to make use of the visible features effectively and not to produce aesthetic interference effects masking information in a screen, the visualization creators should become aware of the attentive duties and the pre-attentive visual features like size, width, hue, level, lighting direction, etc.

Data Foundation

The very main step of visualization is the data to visualise. It really is a must to explore and look at the characteristics of the data since it could be from a variety of kinds of options and has a multitude of characteristics and features.

Data Types

Data can be differentiated into two main types: ordinal (numeric beliefs) and nominal (non-numeric worth). [2]

To be specific, ordinal worth mean

Binary beliefs - those with only 0s and 1s

Discrete ideals - integer prices from a very particular division

Continuous - real values

Nominal principles are

Categorical - principles from list of possibilities

Ranked - categorical factors with significant ordering

Arbitrary - infinite range of prices without significant ordering

Scale is another useful technique of sorting data variables since each graphical attribute from natural data possesses size associated with it. You will find three capabilities of range

Ordering relationship - placed nominal variables and ordinal factors which is often ordered in some manner

Distance metric - all ordinal variables where the distances of different data can be calculated

Existence of overall zero - variables with fixed lowest value

Data Pre-processing

In reality, real life data that is usually to be examined can be imperfect, loud, incoherent and cumulative. Those natural data need to be transformed somehow into an understandable format and the procedure of its change is known as data pre-processing. Data pre-processing can greatly improve the quality of data visualization results. There are a few different facets of data pre-processing

Metadata and statistical

Missing prices and data cleansing

Normalization

Segmentation

Sampling and sub-setting

Dimension reduction

Mapping nominal measurements to numbers

Aggregation and summarization

Smoothing and filtering

Raster to vector conversion

For more info about data pre-processing techniques refer to [2].

Visualization Approaches for Various kinds of Data

Visualization techniques will be differed for different kinds of data since they include special characteristics. Main types of data and useful visualization options for them will be mentioned in this section.

Spatial Data

Spatial capabilities identify data in 1, 2 or multi sizing. Visualizing spatial data is thought as mapping spatial data to spatial characteristics on the display screen. [2]

Techniques of visualization of these data include histograms, linear probes, move visualization, vector field visualization, cut plus isosurface, isosurface plus glyphs and so on.

Geospatial Data

Geospatial data or geographic information classifies geographic locations and boundaries in the real world. [8] They include coordinates and topology on the planet. Examples of geospatial data consist of climate, environmental, inexpensive and sociological and credit-based card payment locations.

Visualization ways of such data can be completed using dot maps, pixel maps, network maps, choropleth maps and cartograms. [2]

Multivariate Data

Multivariate data is lists or furniture of data that comes from several variable. It normally doesn't have an precise spatial feature. [2]

Multivariate data can be visualized by point structured techniques like scatter-plots and drive based methods, series centered techniques like graphs, parallel coordinates, andrews curves and radial axis techniques, and region established techniques that are bar graphs, histograms and tabular exhibits. Combination of above techniques are also applied sometimes.

Trees, Graphs and Network

Bertin declares that trees, graphs and network visualization shows the relationships of each data noted, similarities among worth and attributes, mother or father and child nodes, connectedness such as sites between countries surrounding the world, distributed classification and derivation. [9]

Space filling methods, non space filling methods, displaying arbitrary graphs and networks, and node hyperlink graphs are some of the methods for trees and shrubs, graphs and systems visualization. maps, pixel maps, network maps, choropleth maps and cartograms. [2]

Text and Documents

By applying suited visualization techniques, valuable information can be acquired from huge sources of information such as digital libraries, text files from your computer and vast amounts of words in your thesis newspaper. Searching comparable patterns and outliers within the text or documents will be painful without visualization.

Tag clouds, word trees, wording arcs and arc diagrams can be used for visualizing one documents. Visualization practice for collections of documents are self organizing maps, themescapes and file cards. [2]

Interaction Ideas & Techniques

John and his group clarify that connections within data visualization is a helpful framework for transforming the particular users see and how they perceive it. Relationships will enhance visualization images to raised and clean transitions. Brief summary of relationship techniques are discussed as below. [10]

Navigation

It allows the users to change the camera's position and scale the vision. For example panning, spinning and zooming.

Selection

Selection relates categorizing an object or choices of objects. To get precise, it grants the user to regulate the regions of interest. Highlighting, deleting and modifying are types of selection.

Filtering

The size of data mapped on the display is reduced by filtering techniques by lowering or omitting dataset, sizes or both.

Reconfiguring

It is to improve the way examined data is mapped to visualization visual capabilities like reordering data layouts to be able to provide a diverse way of viewing data.

Encoding

Users are permitted to control graphical characteristics such as point size, brand colors to discover different features of visualization.

Connecting

Connecting means linking different views or things.

Abstracting and Elaborating

It is to modify the level of detail.

Hybrid

Hybrid defines combining these techniques alongside one another.

Effective Visualization

In simple fact, visualizations put in place by the designers have greater risks of being ineffective than being effective. It isn't very simple to build effective visualizations where in fact the users gratify as there are many likelihood of data being distorted and lost through the mapping process, or data provided is too confusing and intricate for the users to interpret, and so on. A successful and effective visualization efficiently and effectively transmits the most well-liked information to the audiences. Therefore, the designers should take in consideration of what the targeted users actually want to watch from the results so that they will be able to visualize effectively.

Intuitive Data Mappings

Ed H. Chi explains that it's necessary to consider the importance of data semantics and the framework of an individual. [11] In order to avoid any misinterpretation, the designers should be able to anticipate the user's targets. Choosing data-to-graphics mappings that provides the user's mental model will significantly support in interpretation. The artist should observe the compatibility between level of data and visual characteristics on the display. Besides, they need to utilize humans' skills to correlate position on the display medium with position in real life.

Selecting and Modifying Views

It is obvious any particular one view is barely satisfactory expressing all the information enclosed in the dataset. Expecting the view improvements which are most readily useful to the users is one of the major factors of growing an effective visualization. Common view functions are the following. [2]

Scrolling and Zooming Operations

This operation will come in useful when the dataset is too huge to be shown as one full at the resolution that the audience wants.

Color Map Control

It allows an individual to make changes of individual feature colors or whole palette.

Mapping Control

Mapping control helps the visitors to toggle among various ways of visualizing the same data and also to discover the different features that will be hidden.

Scale Control

The individual can concentrate on specific data subsets by applying scale control where they can adjust the range and circulation of values.

Information Density

The designer's decision, to confirm how much information to show, takes on an important role for an effective visualization and representation. Alexandru [12] points out that when there is too little information to provide, it's the best to display the results as content material. Conversely, if the data has too much information to provide, it might cause distress, lose essential information within the info, and face with obscurities in interpretation. In such instances, an individual should be permitted to disable or allow different components of the display.

Keys, Product labels and Legends

Most of the visualizations are inadequate because they lack useful and backed information to assist them. [2] Tips, labels and legends are therefore very helpful. For example captions, mappings used, grid marks, systems of axes, key for symbols, color bar and etc.

Using Color with Care

Color can truly add significant overall look to a visualization but can also significantly decrease the efficiency of the communication process. [2] Using color is context centered and the characteristics of dataset itself can influence how the colors are noticeable. The designers shouldn't forget there could be some color blind users as well.

The Need for Aesthetics

Visuals, with both educational and satisfying to the attention, are known as the best representations. In case the visualization is visually pleasant, it appeals to the viewers to analyze it in increased details. [2] Some useful rules for attractive visualization designs are as below.

Focus

The user's attention should be drawn for the most vital area of the visualization.

Balance

Balancing the screen space is another aspect to take note of developing pleasing visualizations. The main components should be positioned in the center.

Simplicity

Representing too much information will confuse the audiences. The designers should get rid of features which is often removed without burning off information wanted to spread since it's the better to be as simple as possible.

Misleading Visualizations

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