Visualization has its roots in a long historical tradition of representing information using primitive paintings and maps on walls, tables of numbers, and paintings on clay. However, they were not known as visualization or data visualization. Data visualization is a new term; it expresses the idea that it involves more than just representing data in a graphical form. The information behind the data should be revealed in an intuitive representation using good display; the graphic should inherently aid viewers in seeing the structure of data.
In early Babylonian times, pictures were drawn on clay and in the later periods were rendered on papyrus. The goal of those paintings and maps was to provide the viewer with a qualitative understanding of the information. We also know that understanding pictures are our natural instincts as a visual presentation of information is perceived with greater ease. This section includes only partial details about the history of visualization. For elaborate details and examples, we recommend two interesting resources:
Data visualization (http://euclid.psych.yorku.ca/datavis/)
The work of Edward Tufte and Graphics Press (www.edwardtufte.com/tufte)
Charles Minard was a civil engineer working in Paris. He summarized the War of 1812—Napoleon's march on Moscow—in a figurative map. This map is a simple picture, which is both a visual timeline and a geographic map depicting the size and direction of the army, temperature, and the landmarks and locations. Prof. Edward Tufte famously described this picture as possibly being the best statistical graphic ever drawn.
The wedge starts with being thick on the left-hand side, and we see the army begin the campaign at the Polish border with 422,000 men. The wedge becomes narrower as it gets deeper into Russia and the temperature gets lower. This visualization manages to condense a number of different numeric and geographic facts into one image: when the army gets reduced, the reason for the reduction, and subsequently, their retreat.
In October 1831, the first case of Asiatic cholera occurred in Great Britain, and over 52,000 people died in the epidemic. Subsequently, in 1848-1849 and 1853-1854, more cholera epidemics produced large death tolls.
In 1855, Dr. John Snow produced a map showing the deaths due to cholera clustered around the Broad Street pump in London. This map by Dr. John Snow was a landmark graphic discovery, but unfortunately, it was devised at the end of that period. His map showed the location of each of the deceased, and that provided an insight for his conclusion that the source of outbreak could be localized to contaminated water from a pump on Broad Street. Around that time, the use of graphs became important in economic and state planning.
By the mid 18th century, a rapid growth of visualization had been established throughout Europe. In 1863, one page of Galton's multivariate weather chart of Europe showed barometric pressure, wind direction, rain, and temperature for the month of December 1861 (source: The life, letters and labors of Francis Galton, Cambridge University Press).
During this period, statistical graphics became mainstream and there were many textbooks written on the same. These textbooks contained detailed descriptions of the graphic method, discussing frequencies, and the effects of the choice of scales and baselines on the visual estimation of differences and ratios. They also contained historical diagrams in which two or more time series could be shown on a single chart for comparative views of their histories.
In the year 1962, John W. Tukey issued a call for the recognition of data analysis as a legitimate branch of statistics; shortly afterwards, he began the invention of a wide variety of new, simple, and effective graphic displays under the rubric Exploratory Data Analysis (EDA), which was followed by Exploratory Spatial Data Analysis (ESDA). Tukey later wrote a book titled Exploratory Data Analysis in 1977. There are a number of tools that are useful for EDA with graphical techniques, which are listed as follows:
Box-and-whisker plot (box plot)
Histogram
Multivari chart (from candlestick charts)
Run-sequence plot
Pareto chart (named after Vilfredo Pareto)
Scatter plot
Multidimensional scaling
Targeted projection pursuit
Visualization in scientific computing is emerging as an important computer-based field, with the goal to improve the understanding of data and to make quick real-time decisions. Today, the ability of medical doctors to diagnose ailments is dependent upon vision. For example, in hip-replacement surgeries, custom hips can now be fabricated before surgical procedures. Accurate measurements can be made prior to surgery using non-invasive 3D imaging thereby reducing the number of post-operative body rejections from 30 percent to a mere 5 percent (source: http://bonesmart.org/hip/hip-implants-specialized-and-custom-fitted-options/).
Visualization of the human brain structure and function in 3D is a research frontier of far-reaching importance. Few advances have transformed the fields of neuroscience and brain-imaging technology, like the ability to see inside and read the brain of a living human. For continued progress in brain research, it will be necessary to integrate structural and functional information at many levels of abstraction.
The rate at which the hardware performance power has been on the rise tells us that we are already able to analyze DNA sequences and visually represent them. The future advances in computing promises a much brighter progress in the fields of medicine and other scientific areas.