VISUALIZATION ON DECISION MAKING AND UNDERSTANDING
With today’s complex ideas and situations individuals need tools to succeed. With the help of information visualization individuals can see information visually improving their chance for success while increasing their understanding of the information. This report will look into the history, types, usage and benefits of information visualization.
History of Information Visualization
Information visualization is the use of images to represent data (Few 2). Information visualization goes as far back as the 2nd century. Egyptians used information visualization, specifically a table, to organize astronomical configurations to make navigation easier (Few 2). The next big step in information visualization was graphs. Graphs weren’t created until the 17th century by the French philosopher and mathematician Rene Decartes. Rene Decartes invented a mathematic way to represent quantitative data based on a system of coordinates (Few 3). The types of graphs that Rene Decartes created aren’t the graphs that today’s society are accustom to. It wasn’t until the late 18th and early 19th century when a Scottish social scientist by the name of William Playfair created the type of graphs, bar charts, and pie charts that we are accustom to today (Few 3). The next big step in information visualization history took place in 1977 when John Tukey, a statistics professor at Princeton University, introduced the use of information visualization as means of exploring and making sense of data (Few 3). One of the final big advancements for information visualization came from the creation of computers. Software programs have created programs that help create multiple types of information visualization, some of which will be discuss later in this report. These programs allow information visualizations to be created much easier and faster than traditional methods. This ease of creation has lead to good and bad trends with information visualization.
Information visualization has been becoming a popular area of study at many universities. Some universities are researching ways toward improving information visualizations in fields such as computer sciences, psychology, and business (Few 4). This research has led to improvements in visual analysis software. Visual analysis software allow its users to represent data graphically, change the nature of the display, filter out irrelevant data, drill into lower levels of detail, and pick out subsets of data across multiple graphs (Few 4). This allows graphs to stimulate our sense of sight and assists us in understanding the information, much better than traditional methods of dispensing information.
Though information visualization is intended to help clarify data, it occasionally tends to make data more complicated. This situation happens when software vendors try to rush the production of visualization software or an upgrade to an existing product without taking time to do it right (Few 8). Creating software that is not user friendly hurts the final product and can lead to confusion. Another bad trend with information visualization is a situation commonly called information overload or data glut, which is when there is too much information in a visualization resulting in confusion (www.ted.com).
TYPES OF INFORMATION VISUALIZATION
There are several different types of information visualizations. Each type of information visualization is used in certain applications for particular reasons. This report will only be examining three types of information visualization, treemapping, hyperbolic trees, and information graphics.
Treemapping is a method of displaying information using nested rectangles (Telea 404). Every rectangle that is located in the visualization is related in some way. These rectangles can have sub-rectangles which are related to that specific...