Data Visualization and Techniques

Akansha Sharma, Prem Pratap Singh

DOI: http://dx.doi.org/10.5138/bjdmn.v5i1.1638

Abstract


Data visualization is the graphical representation of information. Bar charts scatter graphs, and maps are examples of simple data visualizations that have been used for decades. Information technology combines the principles of visualization with powerful applications and large data sets to create sophisticated images and animations. A tag cloud, for instance, uses text size to indicate the relative frequency of use of a set of terms. In many cases, the data that feed a tag cloud come from thousands of Web pages, representing perhaps millions ofusers. All of this information is contained in a simple image that you can understand quickly and easily. More complex visualizations sometimes generate animations that demonstrate how data change over time. In an application called Gap minder, bubbles represent the countriesof the world, with each nationÊs population reflected in the size of its bubble. You can set the x and y axes to compare life expectancy with per capita income, for example, and the tool will show how each nationÊs bubble moves on the graph over time. You can see that higher income generallycorrelates with longer life expectancy, but the visualization also clearly shows that China doesnÊt follow this trend·in 1975, the country had one of the lowest per capita incomes but one of the longer life expectancies. The animation also shows the steep drop in life expectancy in many sub-Saharan African countries starting in the early 1990s (corresponding to the AIDS epidemic in that part of the world) and the plummeting of life expectancy in Rwanda at the time of that nationÊs genocide.

Keywords


Data visualizations, Graph Theory, Data Mining

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