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Data Representations, Transformations, and Statistics for Visual Reasoning [electronic resource] / by Ross Maciejewski.

By: Maciejewski, Ross [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Visualization: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2011Edition: 1st ed. 2011.Description: IX, 75 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031025990.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:
Data Types -- Color Schemes -- Data Preconditioning -- Visual Representations and Analysis -- Summary.
In: Springer Nature eBookSummary: Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making. Recently, the analytical reasoning process has been augmented through the use of interactive visual representations and tools which utilize cognitive, design and perceptual principles. These tools are commonly referred to as visual analytics tools, and the underlying methods and principles have roots in a variety of disciplines. This chapter provides an introduction to young researchers as an overview of common visual representations and statistical analysis methods utilized in a variety of visual analytics systems. The application and design of visualization and analytical algorithms are subject to design decisions, parameter choices, and many conflicting requirements. As such, this chapter attempts to provide an initial set of guidelines for the creation of the visual representation, including pitfalls and areas where the graphics can be enhanced through interactive exploration. Basic analytical methods are explored as a means of enhancing the visual analysis process, moving from visual analysis to visual analytics. Table of Contents: Data Types / Color Schemes / Data Preconditioning / Visual Representations and Analysis / Summary.
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Data Types -- Color Schemes -- Data Preconditioning -- Visual Representations and Analysis -- Summary.

Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making. Recently, the analytical reasoning process has been augmented through the use of interactive visual representations and tools which utilize cognitive, design and perceptual principles. These tools are commonly referred to as visual analytics tools, and the underlying methods and principles have roots in a variety of disciplines. This chapter provides an introduction to young researchers as an overview of common visual representations and statistical analysis methods utilized in a variety of visual analytics systems. The application and design of visualization and analytical algorithms are subject to design decisions, parameter choices, and many conflicting requirements. As such, this chapter attempts to provide an initial set of guidelines for the creation of the visual representation, including pitfalls and areas where the graphics can be enhanced through interactive exploration. Basic analytical methods are explored as a means of enhancing the visual analysis process, moving from visual analysis to visual analytics. Table of Contents: Data Types / Color Schemes / Data Preconditioning / Visual Representations and Analysis / Summary.

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