Trends In Interactive Visualization
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Data Visualization
This book discusses the recent trends and developments in the fields of information processing and information visualization. In view of the increasing amount of data, there is a need to develop visualization techniques to make that data easily understandable. Presenting such approaches from various disciplines, this book serves as a useful resource for graduates.
Data Visualization Techniques
Data visualization techniques are a means to manipulate sampled and computed data for comprehensive display. Visualized data can be static or in motion, to provide visual explanations of algorithms or general information. This book draws on examples from a broad selection of subject areas, such as atmospheric sciences or biology, which deal with diverse data analysis and visualization techniques. The various visualization methodologies covered in this book also include moving images as well as static. It is an important source of information for computer graphics software engineers, graduates and researchers who work in the field of visualization techniques. Unique features in this book include: Details of data visualization techniques for scalar, vector and tensor field data and accompanying data structures Explanation of how to express visual images in computational terms and turn these into display, with minimum delay Methodology for "probing" a displayed visualization, in order to elicit more detail Collection of information from several interrelated subject areas in one volume Trends in Software - edited by Balachander Krishnamurthy of AT&T Research - is a sister publication of the journal Software: Practice and Experience
Trends in Interactive Visualization
Author: Elena Zudilova-Seinstra
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-12-17
II Challenges in Data Mapping Part II deals with one of the most challenging tasks in Interactive Visualization, mapping and teasing out information from large complex datasets and generating visual representations. This section consists of four chapters. Binh Pham, Alex Streit, and Ross Brown provide a comprehensive requirement analysis of information uncertainty visualizations. They examine the sources of uncertainty, review aspects of its complexity, introduce typical models of uncertainty, and analyze major issues in visualization of uncertainty, from various user and task perspectives. Alfred Inselberg examines challenges in the multivariate data analysis. He explains how relations among multiple variables can be mapped uniquely into ?-space subsets having geometrical properties and introduces Parallel Coordinates meth- ology for the unambiguous visualization and exploration of a multidimensional geometry and multivariate relations. Christiaan Gribble describes two alternative approaches to interactive particle visualization: one targeting desktop systems equipped with programmable graphics hardware and the other targeting moderately sized multicore systems using pack- based ray tracing. Finally, Christof Rezk Salama reviews state-of-the-art strategies for the assignment of visual parameters in scientific visualization systems. He explains the process of mapping abstract data values into visual based on transfer functions, clarifies the terms of pre- and postclassification, and introduces the state-of-the-art user int- faces for the design of transfer functions.