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Semantic Interaction for Visual Analytics [electronic resource] : Inferring Analytical Reasoning for Model Steering / by Alex Endert.

By: Endert, Alex [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Visualization: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: IX, 89 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031026034.Subject(s): Information visualization | Data structures (Computer science) | Information theory | Data mining | Data and Information Visualization | Data Structures and Information Theory | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 001.4226 Online resources: Click here to access online
Contents:
Acknowledgments -- Introduction -- Fundamentals -- Spatializations for Sensemaking Using Visual Analytics -- Semantic Interaction -- Applications that Integrate Semantic Interaction -- Evaluating Semantic Interaction -- Discussion and Open Challenges -- Conclusion -- References -- Author's Biography.
In: Springer Nature eBookSummary: This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the visual reasoning processes of people with the computation. This methodology affords user interaction on visual data representations that are native to the domain of the data. User interaction in visual analytics systems is critical to enabling visual data exploration. Interaction transforms people from mere viewers to active participants in the process of analyzing and understanding data. This discourse between people and data enables people to understand aspects of their data, such as structure, patterns, trends, outliers, and other properties that ultimately result in insight. Through interacting with visualizations, users engage in sensemaking, a process of developing and understanding relationships within datasets through foraging and synthesis. The book provides a description of the principles of semantic interaction, providing design guidelines for the integration of semantic interaction into visual analytics, examples of existing technologies that leverage semantic interaction, and a discussion of how to evaluate these technologies. Semantic interaction has the potential to increase the effectiveness of visual analytic technologies and opens possibilities for a fundamentally new design space for user interaction in visual analytics systems.
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Acknowledgments -- Introduction -- Fundamentals -- Spatializations for Sensemaking Using Visual Analytics -- Semantic Interaction -- Applications that Integrate Semantic Interaction -- Evaluating Semantic Interaction -- Discussion and Open Challenges -- Conclusion -- References -- Author's Biography.

This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the visual reasoning processes of people with the computation. This methodology affords user interaction on visual data representations that are native to the domain of the data. User interaction in visual analytics systems is critical to enabling visual data exploration. Interaction transforms people from mere viewers to active participants in the process of analyzing and understanding data. This discourse between people and data enables people to understand aspects of their data, such as structure, patterns, trends, outliers, and other properties that ultimately result in insight. Through interacting with visualizations, users engage in sensemaking, a process of developing and understanding relationships within datasets through foraging and synthesis. The book provides a description of the principles of semantic interaction, providing design guidelines for the integration of semantic interaction into visual analytics, examples of existing technologies that leverage semantic interaction, and a discussion of how to evaluate these technologies. Semantic interaction has the potential to increase the effectiveness of visual analytic technologies and opens possibilities for a fundamentally new design space for user interaction in visual analytics systems.

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