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Mobile Data Visualization
Mobile Data Visualization is about facilitating access to and understanding of data on mobile devices.Wearable trackers, mobile phones, and tablets are used by millions of people each day to read weather maps, financial charts, or personal health meters.What is required to create effective visualizations for mobile devices?This book introduces key concepts of mobile data visualization and discusses opportunities and challenges from both research and practical perspectives. Mobile Data Visualization is the first book to provide an overview of how to effectively visualize, analyze, and communicate data on mobile devices.Drawing from the expertise, research, and experience of an international range of academics and practitioners from across the domains of Visualization, Human Computer Interaction, and Ubiquitous Computing, the book explores the challenges of mobile visualization and explains how it differs from traditional data visualization.It highlights opportunities for reaching new audiences with engaging, interactive, and compelling mobile content. In nine chapters, this book presents interesting perspectives on mobile data visualization including: how to characterize and classify mobile visualizations; how to interact with them while on the go and with limited attention spans; how to adapt them to various mobile contexts; specific methods on how to design and evaluate them; reflections on privacy, ethical and other challenges, as well as an outlook to a future of ubiquitous visualization.This accessible book is a valuable and rich resource for visualization designers, practitioners, researchers, and students alike.
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Introduction to Scientific Visualization
AboutThisBook This book was ?rst suggested to Springer in 2004, though its origins go back to changes made two years earlier to the structure of the University of Hull’s Computer Science programme.At the same time, my own visualization - search was leading towards a systematic view of data and techniques that I felt could be educationally valuable.In 2003 I thus sat down with some trepidation to write a visualization course founded on research in the area but nonetheless accessible to students.This course could, however, involve no mathematics beyond GCSE, in line with university admissions practices of that time.Writing the course involved generating many new illustrations, in the form of both line drawings and visualization screenshots and, wi- ing to get maximum mileage out of this e?ort, the idea of writing a book to accompany the course came about.At the University of Hull, our practical visualization teaching is based on IRIS Explorer, an application builder-type package from NAG Ltd. Ori- nally this book was to have been both an introduction to visualization and a handbook for beginners in IRIS Explorer, with ‘virtual laboratories’ running throughout it to illustrate certain points.Following comments from revi- ers, however, its emphasis has changed.
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Visualization Analysis and Design
Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices.The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques for spatial data, and visual analytics techniques for interweaving data transformation and analysis with interactive visual exploration.It emphasizes the careful validation of effectiveness and the consideration of function before form.The book breaks down visualization design according to three questions: what data users need to see, why users need to carry out their tasks, and how the visual representations proposed can be constructed and manipulated.It walks readers through the use of space and color to visually encode data in a view, the trade-offs between changing a single view and using multiple linked views, and the ways to reduce the amount of data shown in each view.The book concludes with six case studies analyzed in detail with the full framework. The book is suitable for a broad set of readers, from beginners to more experienced visualization designers.It does not assume any previous experience in programming, mathematics, human–computer interaction, or graphic design and can be used in an introductory visualization course at the graduate or undergraduate level.
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Information Visualization : Perception for Design
Information Visualization: Perception for Design, Fourth Edition explores the art and science of why we see objects the way we do.Based on the science of perception and vision, the author presents the key principles at work for a wide range of applications--resulting in visualization of improved clarity, utility and persuasiveness.This new edition has been revised and updated to include the latest relevant research findings.Content has been updated in areas such as the cognitive neuroscience of maps and navigation, the neuroscience of pattern perception, and the hierarchy of learned patterns. New changes to the book make it easier to apply perceptual lessons to design decisions.In addition, the book offers practical guidelines that can be applied by anyone, including interaction designers and graphic designers of all kinds.
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Data Visualization : A Practical Introduction
An accessible primer on how to create effective graphics from dataThis 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 ggplot2Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistentIncludes a library of data sets, code, and functions
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Functional Aesthetics for Data Visualization
What happens when a researcher and a practitioner spend hours crammed in a Fiat discussing data visualization?Beyond creating beautiful charts, they found greater richness in the craft as an integrated whole.Drawing from their unconventional backgrounds, these two women take readers through a journey around perception, semantics, and intent as the triad that influences visualization.This visually engaging book blends ideas from theory, academia, and practice to craft beautiful, yet meaningful visualizations and dashboards.How do you take your visualization skills to the next level?The book is perfect for analysts, research and data scientists, journalists, and business professionals.Functional Aesthetics for Data Visualization is also an indispensable resource for just about anyone curious about seeing and understanding data.Think of it as a coffee book for the data geek in you. https://www.functionalaestheticsbook.com
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Modern Data Visualization with R
Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights.It starts with basic graphs such as bar charts, scatter plots, and line charts, but progresses to less well-known visualizations such as tree maps, alluvial plots, radar charts, mosaic plots, effects plots, correlation plots, biplots, and the mapping of geographic data.Both static and interactive graphics are described and the use of color, shape, shading, grouping, annotation, and animations are covered in detail.The book moves from a default look and feel for graphs, to graphs with customized colors, fonts, legends, annotations, and organizational themes. FeaturesContains a wide breadth of graph types including newer and less well-known approachesConnects each graph type to the characteristics of the data and the goals of the analysisMoves the reader from simple graphs describing one variable to building visualizations that describe complex relationships among many variablesProvides newer approaches to creating interactive web graphics via JavaScript librariesDetails how to customize each graph type to meet users’ needs and those of their audiencesGives methods for creating visualizations that are publication ready for print (in color or black and white) and the webSuggests best practicesOffers examples from a wide variety of fieldsThe book is written for those new to data analysis as well as the seasoned data scientist.It can be used for both teaching and research, and will particularly appeal to anyone who needs to describe data visually and wants to find and emulate the most appropriate method quickly.The reader should have some basic coding experience, but expertise in R is not required.Some of the later chapters (e.g., visualizing statistical models) assume exposure to statistical inference at the level of analysis of variance and regression.
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Differential Geometry and Its Visualization
Differential Geometry and Its Visualization is suitable for graduate level courses in differential geometry, serving both students and teachers.It can also be used as a supplementary reference for research in mathematics and the natural and engineering sciences. Differential geometry is the study of geometric objects and their properties using the methods of mathematical analysis.The classical theory of curves and surfaces in three-dimensional Euclidean space is presented in the first three chapters.The abstract and modern topics of tensor algebra, Riemannian spaces and tensor analysis are studied in the last two chapters.A great number of illustrating examples, visualizations and genuine figures created by the authors’ own software are included to support the understanding of the presented concepts and results, and to develop an adequate perception of the shapes of geometric objects, their properties and the relations between them. FeaturesExtensive, full colour visualisationsNumerous exercisesSelf-contained and comprehensive treatment of the topic
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