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Our ability to create data extends far beyond our ability to use it effectively. Through the use of technology we are capturing and storing vast amounts of information describing important aspects of our worlds, and yet our capacity to use this information effectively in timely analysis and decision making is severely limited. Areas in which this presents a problem include (but are not limited to) security, crime, emergency management, medicine and corporate investigations. Visual analytics is a multidisciplinary field aimed at addressing this problem. At its heart lies the idea of interactive visualisations allowing users to seamlessly explore and derive insight from complex datasets to address an operational problem at hand.

It includes:

  • The study of human analytical reasoning involved in making sense of data, often collaboratively, to support conclusions and coordinated action.
  • The design and development of visual representations and interactive technologies necessary to support insight by exploiting our natural ability to identify trends and anomalies in visually represented information;
  • Data representations and transformations necessary to convert data into useful forms, including rudimentary inferences, to enable the natural application of higher-order human reasoning processes.

To date research has been conducted in all of these areas. The challenge for visual analytics is to engage with and harness these perspectives in the production of technological tools which integrate and add value into the real data analysis problems that we face.  

Reference:  James J Thomas & Kristin A Cook (2006) Visual Viewpoints: A visual Analytics Agenda, IEEE Computer Graphics and Applications, 26(1), pp.10-13.