Societies continued reliance on information and communications technologies has resulted in organizations generating, gathering, and storing “raw data” at a rate growing each year. The ability for even a mid-sized organization to store tens to hundreds of terabytes of data is already within reach. Massive storage technologies are rapidly outstripping our ability to effectively analyse, explore, and understand such voluminous data. While research in other fields such as data mining, machine learning and knowledge management are also attempting to aid in the analysis of such voluminous data,
there is a realisation that the “human-in-the-loop” affords a visual analysis not possible through automation alone.
As such, the area of visual analytics extends the fields of scientific and information visualization by incorporating techniques from knowledge management, statistical analysis, cognitive science and decision science. This talk will outline how voluminous data is modeled, managed,
mined and hence visually presented for exploration. Several large scale data and information visualisation methods will be described and discussed along with the a number of challenges and open research questions we face as researchers in using visualisation in an attempt to present information.
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