Highly interactive visual analytics systems

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Visual Analytics (VA) is defined as the science of analytical reasoning facilitated by interactive visual interfaces. In contrast to computation alone, visualization can harness the human mind's innate visual intelligence to gain novel insights into situations characterized by complex data. While methods for creating graphical visualizations are understood, visual analytics (VA) directly addresses the ultimate goal of this process: human reasoning and analysis about complex situations. In this proposal, I aim to develop a new architectural model of Visual Analytics software that more directly takes into account the various cognitive activities that analysts engage in during the analysis of large collections of documents. Currently, established practice for examining large data collections is to use information retrieval tools to analyze a document set for trends and to search for evidence that supports hypotheses that may arise from examining the documents. Information visualization tools such as maps are plotted with time-coded events to visualize the movement of people across a city, for example. The strength of these visual tools is that they supply a means of external cognition: they augment internal cognitive processes with concrete spatial representations of relationships of interest that can be referred to later. The drawback of current visual tools is that they do not themselves offer much direct support for more "high level" cognitive activity. Many significant analysis tasks take place over a long period of time and must be shared among many people. In my discussions with intelligence analysts, there has been a frequent call for systems that are capable of recapitulating key points of past analyses, and for the re-use of analytical steps on new or updated data. This proposal focuses on the design and development of new models and software to aid in the analysis process. The first new element of this work is to provide an editable and re-playable history navigation channel in addition to multiple visual representations of document collections and the entities within them.