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The Visualization Handbook provides an overview of the field of visualization by presenting the basic concepts, providing a snapshot of current visualization software systems, and examining research topics that are advancing the field. This text is intended for a broad audience, including not only the visualization expert seeking advanced methods to solve a particular problem, but also the novice looking for general background information on visualization topics. The largest collection of state-of-the-art visualization research yet gathered in a single volume, this book includes articles by a “who’s who of international scientific visualization researchers covering every aspect of the discipline, including:· Virtual environments for visualization· Basic visualization algorithms· Large-scale data visualization· Scalar data isosurface methods· Visualization software and frameworks· Scalar data volume rendering· Perceptual issues in visualization· Various application topics, including information visualization. * Edited by two of the best known people in the world on the subject; chapter authors are authoritative experts in their own fields;* Covers a wide range of topics, in 47 chapters, representing the state-of-the-art of scientific visualization.
The data visualization handbook is a practical guide to creating compelling graphics to explain or explore data. It is primarily aimed for designers, journalists, researchers, analysts, and other professionals who want to learn the basics of visualization, but also includes plenty of material for people with intermediate level visualization skills.
Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. This book gives an overview of modern data visualization methods, both in theory and practice. It details modern graphical tools such as mosaic plots, parallel coordinate plots, and linked views. Coverage also examines graphical methodology for particular areas of statistics, for example Bayesian analysis, genomic data and cluster analysis, as well software for graphics.
One of the "six best books for data geeks" - Financial Times With over 200 images and extensive how-to and how-not-to examples, this new edition has everything students and scholars need to understand and create effective data visualisations. Combining ‘how to think’ instruction with a ‘how to produce’ mentality, this book takes readers step-by-step through analysing, designing, and curating information into useful, impactful tools of communication. With this book and its extensive collection of online support, readers can: Decide what visualisations work best for their data and their audience using the chart gallery See data visualisation in action and learn the tools to try it themselves Follow online checklists, tutorials, and exercises to build skills and confidence Get advice from the UK’s leading data visualisation trainer on everything from getting started to honing the craft.
With contributions from some of the world's leading experts, the second edition of this classic reference compiles all major techniques of flow visualization and demonstrates their applications in all fields of science and technology. A new chapter has been added that covers flow visualization applications in large wide tunnels for airplane and automobile testing. Several important examples of applications are included. A second new chapter details the use of infrared (IR) cameras for detecting and observing the boundary layer transition in industrial wind tunnels and flight testing of commercial transport airplanes. A final new chapter has been added on multiphase flow and pulsed-light velocimetry.
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story
An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions
Visualizations are visual representations of non-visual data. They are produced for people to interact with and to make sense of the underlying data. Rapid advances in display technology and computer power have enabled researchers to produce visually appealing pictures. However, the effectiveness of those pictures in conveying the embedded information to end users has not been fully explored. Handbook of Human Centric Visualization addresses issues related to design, evaluation and application of visualizations. Topics include visualization theories, design principles, evaluation methods and metrics, human factors, interaction methods and case studies. This cutting-edge book includes contributions from well-established researchers worldwide, from diverse disciplines including psychology, visualization and human-computer interaction. This handbook is designed for a professional audience composed of practitioners, lecturers and researchers working in the field of computer graphics, visualization, human-computer interaction and psychology. Undergraduate and postgraduate students in science and engineering focused on this topic will also find this book useful as a comprehensive textbook or reference.