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DOE OSTI · 1158968

Semantic Interaction for Visual Analytics: Toward Coupling Cognition and Computation

Endert, Alexander
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Abstract

The dissertation discussed in this article [1] was written in the midst of an era of digitization. The world is becoming increasingly instrumented with sensors, monitoring, and other methods for generating data describing social, physical, and natural phenomena. Thus, data exist with the potential of being analyzed to uncover, or discover, the phenomena from which it was created. However, as the analytic models leveraged to analyze these data continue to increase in complexity and computational capability, how can visualizations and user interaction methodologies adapt and evolve to continue to foster discovery and sensemaking?

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BibTeXRIS

Endert, Alexander. 2014-07-01. Semantic Interaction for Visual Analytics: Toward Coupling Cognition and Computation. https://doi.org/10.1109/mcg.2014.73

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Toward Usable Interactive Analytics: Coupling Cognition and Computation

Interactive analytics provide users a myriad of computational means to aid in extracting meaningful information from large and complex datasets. Much prior work focuses either on advancing the capabilities of machine-centric approaches by the data mining and machine learning communities, or human-driven methods by the visualization and CHI communities. However, these methods do not yet support a true human-machine symbiotic relationship where users and machines work together collaboratively and adapt to each other to advance an interactive analytic process. In this paper we discuss some of the inherent issues, outlining what we believe are the steps toward usable interactive analytics that will ultimately increase the effectiveness for both humans and computers to produce insights.

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