From Visualization to Visually Enabled Reasoning


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MEYER, Joerg, Jim THOMAS, Stephan DIEHL, Brian FISHER, Daniel A. KEIM, 2010. From Visualization to Visually Enabled Reasoning. In: HAGEN, Hans, ed.. Scientific Visualization : Advanced Concepts. Wadern:Schloss Dagstuhl : Leibniz-Zentrum für Informatik GmbH, pp. 227-245. ISBN 978-3-939897-19-4. Available under: doi: 10.4230/DFU.SciViz.2010.227

@incollection{Meyer2010Visua-40709, title={From Visualization to Visually Enabled Reasoning}, year={2010}, doi={10.4230/DFU.SciViz.2010.227}, number={Vol . 1}, isbn={978-3-939897-19-4}, address={Wadern}, publisher={Schloss Dagstuhl : Leibniz-Zentrum für Informatik GmbH}, series={Dagstuhl Follow-Ups}, booktitle={Scientific Visualization : Advanced Concepts}, pages={227--245}, editor={Hagen, Hans}, author={Meyer, Joerg and Thomas, Jim and Diehl, Stephan and Fisher, Brian and Keim, Daniel A.} }

From Visualization to Visually Enabled Reasoning Meyer, Joerg Fisher, Brian Meyer, Joerg Diehl, Stephan Thomas, Jim Fisher, Brian 2010 2017-11-22T11:24:31Z Keim, Daniel A. Interactive Visualization has been used to study scientific phenomena, analyze data, visualize information, and to explore large amounts of multi-variate data. It enables the human mind to gain novel insights by empowering the human visual system, encompassing the brain and the eyes, to discover properties that were previously unknown. While it is believed that the process of creating interactive visualizations is reasonably well understood, the process of stimulating and enabling human reasoning with the aid of interactive visualization tools is still a highly unexplored field.<br />We hypothesize that visualizations make an impact if they successfully influence a thought process or a decision. Interacting with visualizations is part of this process. We present exemplary cases where visualization was successful in enabling human reasoning, and instances where the interaction with data helped in understanding the data and making a better informed decision.<br />We suggest metrics that help in understanding the evolution of a decision making process. Such a metric would measure the efficiency of the reasoning process, rather than the performance of the visualization system or the user. We claim that the methodology of interactive visualization, which has been studied to a great extent, is now sufficiently mature, and we would like to provide some guidance regarding the evaluation of knowledge gain through visually enabled reasoning. It is our ambition to encourage the reader to take on the next step and move from information visualization to visually enabled reasoning. 2017-11-22T11:24:31Z eng Keim, Daniel A. Diehl, Stephan Thomas, Jim

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