Data Visualization Representing Information On Modern Web

Unleash the power of data by creating interactive, engaging, and compelling visualizations for the web About This Book Get a portable, versatile, and flexible data visualization design approach that will help you navigate the complex path towards success Get thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options A comprehensive and contemporary introduction to data-driven visualization design and the most effective approaches to designing impact-maximizing and cognition-amplifying visualizations Who This Book Is For This course is for developers who are excited about data and who want to share that excitement with others and it will be handy for the web developers or data scientists who want to create interactive visualizations for the web. Prior knowledge of developing web applications is required. You should have a working knowledge of both JavaScript and HTML. What You Will Learn Harness the power of D3 by building interactive and real-time data-driven web visualizations Find out how to use JavaScript to create compelling visualizations of social data Identify the purpose of your visualization and your project's parameters to determine overriding design considerations across your project's execution Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics Explore the various features of HTML5 to design creative visualizations Discover what data is available on Stack Overflow, Facebook, Twitter, and Google+ Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for server using Node.js In Detail Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. After getting familiar with key concepts of data visualization, it's time to incorporate it with various technologies. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations. It also clears up how the often complicated OAuth protocol works to help you unlock a universe of social media data from sites such as Twitter, Facebook, and Google+. Once you are familiar with the concepts of incorporating data visualization with HTML5 and JavaScript, third module, Learning d3.js Data Visualization, will lead you to D3, which has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. This module provides a strong foundation in designing compelling web visualizations with D3.js. By the end of this course, you will have unlocked the mystery behind successful data visualizations. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Data Visualization: a successful design process by Andy Kirk Social Data Visualization with HTML5 and JavaScript by Simon Timms Learning d3.js Data Visualization, Second Edition by Ǯdrew Rininsland and Swizec Teller Style and approach This course includes all the resources that will help you jump into creating interactive and engaging visualizations for the web. Through this comprehensive course, you'll learn how to create engaging visualizations for the web to represent your data from start to finish!

Unleash the power of data by creating interactive, engaging, and compelling visualizations for the web About This Book Get a portable, versatile, and flexible data visualization design approach that will help you navigate the complex path towards success Get thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options A comprehensive and contemporary introduction to data-driven visualization design and the most effective approaches to designing impact-maximizing and cognition-amplifying visualizations Who This Book Is For This course is for developers who are excited about data and who want to share that excitement with others and it will be handy for the web developers or data scientists who want to create interactive visualizations for the web. Prior knowledge of developing web applications is required. You should have a working knowledge of both JavaScript and HTML. What You Will Learn Harness the power of D3 by building interactive and real-time data-driven web visualizations Find out how to use JavaScript to create compelling visualizations of social data Identify the purpose of your visualization and your project's parameters to determine overriding design considerations across your project's execution Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics Explore the various features of HTML5 to design creative visualizations Discover what data is available on Stack Overflow, Facebook, Twitter, and Google+ Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for server using Node.js In Detail Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. After getting familiar with key concepts of data visualization, it's time to incorporate it with various technologies. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations. It also cle...

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

Information may be beautiful, but our decisions about the data we choose to represent and how we represent it are never neutral. This insightful history traces how data visualization accompanied modern technologies of war, colonialism and the management of social issues of poverty, health and crime. Discussion is based around examples of visualization, from the ancient Andean information technology of the quipu to contemporary projects that show the fate of our rubbish and take a participatory approach to visualizing cities. This analysis places visualization in its theoretical and cultural contexts, and provides a critical framework for understanding the history of information design with new directions for contemporary practice.

Provides information on the methods of visualizing data on the Web, along with example projects and code.

Turn your raw data into real knowledge by creating and deploying complex data visualizations with D3.js About This Book Understand how to best represent your data by developing the right kind of visualization Explore the concepts of D3.js through examples that enable you to quickly create visualizations including charts, network diagrams, and maps Get practical examples of visualizations using real-world data sets that show you how to use D3.js to visualize and interact with information to glean its underlying meaning Who This Book Is For Whether you are new to data and data visualization, a seasoned data scientist, or a computer graphics specialist, this Learning Path will provide you with the skills you need to create web-based and interactive data visualizations. Some basic JavaScript knowledge is expected, but no prior experience with data visualization or D3 is required What You Will Learn Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for servers using Node.js Install and use D3.js to create HTML elements within a document Create and style graphical elements such as circles, ellipses, rectangles, lines, paths, and text using SVG Turn your data into bar and scatter charts, and add margins, axes, labels, and legends Use D3.js generators to perform the magic of creating complex visualizations from data Add interactivity to your visualizations, including tool-tips, sorting, hover-to-highlight, and grouping and dragging of visuals Write, test, and distribute a D3-based charting package Make a real-time application with Node and D3 In Detail D3 has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. We begin the course by setting up a strong foundation, then build on this foundation as we take you through the entire world of reimagining data using interactive, animated visualizations created in D3.js. In the first module, we cover the various features of D3.js to build a wide range of visualizations. We also focus on the entire process of representing data through visualizations. By the end of this module, you will be ready to use D3 to transform any data into a more engaging and sophisticated visualization. In the next module, you will learn to master the creation of graphical elements from data. Using practical examples provided, you will quickly get to grips with the features of D3.js and use this learning to create your own spectacular data visualizations with D3.js. Over the last leg of this course, you will get acquainted with how to integrate D3 with mapping libraries to provide reverse geocoding and interactive maps among many other advanced features of D3. This module culminates by showing you how to create enterprise-level dashboards to display real-time data. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning D3.js Data Visualization, Second Edition by Andrew H. Rininsland D3.js By Example by Michael Heydt Mastering D3.js by Pablo Navarro Castillo Style and approach This course provides a comprehensive explanation of how to leverage the power of D3.js to create powerful and creative visualizations through step-by-step instructions in the form of modules. Each module help you skill up a level in creating meaningful visualizations.

Data visualization is currently a very active and vital area of research, teaching and development. The term unites the established field of scientific visualization and the more recent field of information visualization. The success of data visualization is due to the soundness of the basic idea behind it: the use of computer-generated images to gain insight and knowledge from data and its inherent patterns and relationships. A second premise is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes, and simulations involving data sets from diverse scientific disciplines and large collections of abstract data from many sources. These concepts are extremely important and have a profound and widespread impact on the methodology of computational science and engineering, as well as on management and administration. The interplay between various application areas and their specific problem solving visualization techniques is emphasized in this book. Reflecting the heterogeneous structure of Data Visualization, emphasis was placed on these topics: -Visualization Algorithms and Techniques; -Volume Visualization; -Information Visualization; -Multiresolution Techniques; -Interactive Data Exploration. Data Visualization: The State of the Art presents the state of the art in scientific and information visualization techniques by experts in this field. It can serve as an overview for the inquiring scientist, and as a basic foundation for developers. This edited volume contains chapters dedicated to surveys of specific topics, and a great deal of original work not previously published illustrated by examples from a wealth of applications. The book will also provide basic material for teaching the state of the art techniques in data visualization. Data Visualization: The State of the Art is designed to meet the needs of practitioners and researchers in scientific and information visualization. This book is also suitable as a secondary text for graduate level students in computer science and engineering.

Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.