Example Reflection – Visualization

1.Challenge and Selection :

Data visualization is also regarded as information visualization or scientific visualization. Human  beings have always employed visualizations to make messages or information last in time. The first tool I  used was the tool of Visualization, or Visual Thinking, to achieve a shared understanding of a problem  space among a diverse group of stakeholders before attempting to identify and define possible solutions  to the problem. I use this approach often with our customers, who are government agencies working to  apply technology innovations to modernize their mission or the delivery of their services to their  customer.

2. Visualization Techniques :

Visualization is the use of computer-supported, visual representation of data. Unlike static data  visualization, interactive data visualization allows users to specify the format used in displaying data.  Data visualization uses computer graphics to show patterns, trends, and relationship among elements of  the data. It can generate pie charts, bar charts, scatter plots, and other types of data graphs with simple  pull-down menus and mouse clicks. Colors are carefully selected for certain types of visualization. When  color is used to represent data, we must choose effective colors to differentiate between data elements.

3. .Visualization Approach  :

In data visualization, data is abstracted and summarized. Spatial variables such as position, size, and  shape represent key elements in the data. A visualization system should perform a data reduction,  transform and project the original dataset on a screen. Visualization of large data sets is a demanding  task, especially if different users are interested in different aspects of the same data set. Today’s  visualization techniques often do not distinguish different aspects and thus visualize all aspects of the  data, which leads to overcrowded and cluttered representations. Moreover, users are provided with  information irrelevant to them.

4.Principles of Visualization :

Through the use of visualization principles much value can be given to a graphic. This value comes in the  form of the stimulation received from the graphic which helps to give the viewer an understanding of  the visual that would have been difficult to convey otherwise.

The first visual variable is position, these represent changes in the x, y, and z (if z coordinates exist)  coordinates on the graphic. Following that is size, which can represent a change in length or area. Third  is shape. Value, which is fourth, represents a change from light to dark. Next is orientation, this shows a  change in alignment. Colour is another visual variable and can take on as many values as the eye can  distinguish.

5.Applications of Visualization :

Most visualization designs are to aid decision making and serve as tools that augment cognition. In  designing and building a data visualization prototype, one must be guided by how the visualization will  be applied. Data visualization is more than just representing numbers; it involves selecting and  rethinking the numbers on which the visualization is based.

Visualization techniques are used for data analysis. When  Visualization techniques are first off all, it  should be observed the relevant characteristics of the data such as: data type, dimensionality (number  of attributes) and scalability (number of records).

Visualization of data is an important branch of computer science and has wide range of application  areas. Several application-specific tools have been developed to analyze individual datasets in many  fields of medicine and science.


Example Reflection – Visualization 1.Challenge and Selection : Data visualization is also regarded as information visualization or scientific visualization . Human beings have always employed visualizations to make messages or information last in time . The first tool I used was the tool of Visualization , or Visual Thinking , to achieve a shared understanding of a problem space among a diverse group of stakeholders before attempting to identify and define possible solutions to the problem . I use this approach often with our customers , who are government agencies working to apply technology innovations to modernize their mission or the delivery of their services to their customer . 2 . Visualization Techniques : Visualization is the use of computer - supported , visual representation of data . Unlike static data visualization , interactive data visualization allows users to specify the format used in displaying data . Data visualization uses computer graphics to show patterns , trends , and relationship among elements of the data . It can generate pie charts , bar charts , scatter plots , and other types of data graphs with simple pull - down menus and mouse clicks . Colors are carefully selected for certain types of visualization . When color is used to represent data , we must choose effective colors to differentiate between data elements . 3 . .Visualization Approach : In data visualization , data is abstracted and summarized . Spatial variables such as position , size , and shape represent key elements in the data . A visualization system should perform a data reduction , transform and project the original dataset on a screen . Visualization of large data sets is a demanding task , especially if different users are interested in different aspects of the same data set . Today ’s visualization techniques often do not distinguish different aspects and thus visualize all aspects of the data , which leads to overcrowded and cluttered representations . Moreover , users are provided with information irrelevant to them . 4.Principles of Visualization : Through the use of visualization principles much value can be given to a graphic . This value comes in the form of the stimulation received from the graphic which helps to give the viewer an understanding of the visual that would have been difficult to convey otherwise . The first visual variable is position , these represent changes in the x , y , and z ( if z coordinates exist ) coordinates on the graphic . Following that is size , which can represent a change in length or area . Third is shape . Value , which is fourth , represents a change from light to dark . Next is orientation , this shows a change in alignment . Colour is another visual variable and can take on as many values as the eye can distinguish . 5.Applications of Visualization : Most visualization designs are to aid decision making and serve as tools that augment cognition . In designing and building a data visualization prototype , one must be guided by how the visualization will be applied . Data visualization is more than just representing numbers ; it involves selecting and rethinking the numbers on which the visualization is based . Visualization techniques are used for data analysis . When Visualization techniques are first off all , it should be observed the relevant characteristics of the data such as : data type , dimensionality ( number of attributes ) and scalability ( number of records ) . Visualization of data is an important branch of computer science and has wide range of application areas . Several application - specific tools have been developed to analyze individual datasets in many fields of medicine and science .