Create and publish your own interactive data visualization projects on the Web, even if you have no experience with either web development or data visualization. It’s easy with this hands-on guide. You’ll start with an overview of data visualization concepts and simple web technologies, and then learn how to use D3, a JavaScript library that lets you express data as visual elements in a web page. Interactive Data Visualization for the Web makes these skills available at an introductory level for designers and visual artists without programming experience, journalists interested in the emerging data journalism processes, and others keenly interested in visualization and publicly available data sources. Get a practical introduction to data visualization, accessible for beginners Focus on web-based tools that help you publish your creations quickly to a wide audience Learn about interactivity so you can engage users in exploring your data

In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data. The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today’s large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis. The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains. Features: Dedicated to the synthesis of visual, interactive, and analysis methods Systematic top-down view on visualization, interaction, and automatic analysis Broad coverage of fundamental and advanced visualization techniques Comprehensive chapter on interacting with visual representations Extensive integration of automatic computational methods Accessible portrayal of cutting-edge visual analytics technology Foreword by Jack van Wijk For more information, you can also visit the author website, where the book's figures are made available under the CC BY Open Access license.

A guide to fundamental issues in designing interactive visualizations, exploring ideas of inquiry, design, structured data, and usability. Interactive visualization is emerging as a vibrant new form of communication, providing compelling presentations that allow viewers to interact directly with information in order to construct their own understandings of it. Building on a long tradition of print-based information visualization, interactive visualization utilizes the technological capabilities of computers, the Internet, and computer graphics to marshal multifaceted information in the service of making a point visually. This book offers an introduction to the field, presenting a framework for exploring historical, theoretical, and practical issues. It is not a “how-to” book tied to specific and soon-to-be-outdated software tools, but a guide to the concepts that are central to building interactive visualization projects whatever their ultimate form. The framework the book presents (known as the ASSERT model, developed by the author), allows the reader to explore the process of interactive visualization in terms of choosing good questions to ask; finding appropriate data for answering them; structuring that information; exploring and analyzing the data; representing the data visually; and telling a story using the data. Interactive visualization draws on many disciplines to inform the final representation, and the book reflects this, covering basic principles of inquiry, data structuring, information design, statistics, cognitive theory, usability, working with spreadsheets, the Internet, and storytelling.

"This is a book about what the science of perception can tell us about visualization. There is a gold mine of information about how we see to be found in more than a century of work by vision researchers. The purpose of this book is to extract from that large body of research literature those design principles that apply to displaying information effectively"--

Visualization has become a valuable means for data exploration and analysis. Interactive visualization combines expressive graphical representations and effective user interaction. Although interaction is an important component of visualization approaches, much of the visualization literature tends to pay more attention to the graphical representation than to interaction. The goal of this work is to strengthen the interaction side of visualization. Based on a brief review of general aspects of interaction, we develop an interaction-oriented view on visualization. This view comprises five key aspects: the data, the tasks, the technology, the human, as well as the implementation. Picking up these aspects individually, we elaborate several interaction methods for visualization. We introduce a multi-threading architecture for efficient interactive exploration. We present interaction techniques for different types of data e.g., multivariate data, spatio-temporal data, graphs) and different visualization tasks (e.g., exploratory navigation, visual comparison, visual editing). With respect to technology, we illustrate approaches that utilize modern interaction modalities (e.g., touch, tangibles, proxemics) as well as classic ones. While the human is important throughout this work, we also consider automatic methods to assist the interactive part. In addition to solutions for individual problems, a major contribution of this work is the overarching view of interaction in visualization as a whole. This includes a critical discussion of interaction, the identification of links between the key aspects of interaction, and the formulation of research topics for future work with a focus on interaction.

The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web programming. Through many R code examples, you will learn how to tap the extensive functionality of these tools to enhance the presentation and exploration of data. By mastering these concepts and tools, you will impress your colleagues with your ability to quickly generate more informative, engaging, and reproducible interactive graphics using free and open source software that you can share over email, export to pdf, and more. Key Features: Convert static ggplot2 graphics to an interactive web-based form Link, animate, and arrange multiple plots in standalone HTML from R Embed, modify, and respond to plotly graphics in a shiny app Learn best practices for visualizing continuous, discrete, and multivariate data Learn numerous ways to visualize geo-spatial data This book makes heavy use of plotly for graphical rendering, but you will also learn about other R packages that support different phases of a data science workflow, such as tidyr, dplyr, and tidyverse. Along the way, you will gain insight into best practices for visualization of high-dimensional data, statistical graphics, and graphical perception. The printed book is complemented by an interactive website where readers can view movies demonstrating the examples and interact with graphics.

Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser.