Now that data analysis is task relegated to the everyday, the processes that serve particular functions related to this task must be simple despite their complexity. Because of the large quantities of data that are generated for any given project, techniques must be developed that allow researchers to “[interpret data] holistically, and to expose meaningful patterns and structure, trends and exceptions, and more”.
The 2010 Horizon Report examines the blending of visualization, data mining, and statistics that has produced the new field of visual data analysis. Essentially, visual data analysis allows data to be placed into any number of charts, maps, tag clouds, or any other graphical means through pattern-matching in relation to human interaction, and the making of meaning from various sets of information. The report draws on tools such as self-organizing maps that “create a grid of ‘neuronal units’ such that neighboring units recognize similar data, reinforcing important patterns so that they can be seen” to prove the usefulness of such a system for the common user.
Although visual data analysis is useful for everything from flow charts to word collages, it also may be a useful tool due to its ability to seek and find patterns within a given text. Another boon involves the ease with which data may be accessed from various sites. Thus, interactive visualizations of data can someday be widely available, which will add to the effectiveness of electronic books and journals, as these visualizations will allow users to draw on and visually map the most up-to-date data available. In this way, “graphical representations, in whatever form they take, will be expected to clarify the narrative in an environment that combines increasingly sophisticated multimedia presentation with ever-increasing amounts and types of data” (http://net.educause.edu/ir/library/pdf/ELI7052.pdf).
For more information, the link to the 2010 Horizon Report is here: http://wp.nmc.org/horizon2010/chapters/visual-data-analysis/. Here also is an example of visual data analysis at work from Gapminder World: