Methods Citations. Results Citations. Figures, Tables, and Topics from this paper. Citation Type. Has PDF.
Publication Type. More Filters. Why Visualize? Untangling a Large Network of Arguments. View 1 excerpt, cites background. Evaluating Visualisations in Voting Advice Applications. View 2 excerpts, cites background. Superpowers as Inspiration for Visualization.
Traditional scatterplots fail to scale as the complexity and amount of data increases. In response, there exist many design options that modify or expand the traditional scatterplot design to meet … Expand. Highly Influenced. View 4 excerpts, cites background and methods. Discriminability Tests for Visualization Effectiveness and Scalability.
View 2 excerpts, cites results and background. View 6 excerpts, cites background and methods. Scatterplots: Tasks, Data, and Designs. View 10 excerpts, cites methods and background. 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. 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. Create and publish your own interactive data visualization projects on the web—even if you have little or no experience with data visualization or web development. This fully updated and expanded second edition takes you through the fundamental concepts and methods of D3, the most powerful JavaScript library for expressing data visually in a web browser.
Ideal for designers with no coding experience, reporters exploring data journalism, and anyone who wants to visualize and share data, this step-by-step guide will also help you expand your web programming skills by teaching you the basics of HTML, CSS, JavaScript, and SVG. Learn D3 4. 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. Exponential increases in available computational resources over the recent decades have fueled an information explosion in almost every scientific field.
This has led to a societal change shifting from an information-poor research environment to an over-abundance of information. As many of these cases involve too much information to directly comprehend, visualization proves to be an effective tool to gain insight into these large datasets. While visualization has been used since the beginning of mankind, its importance is only increasing as the exponential information growth widens the difference between the amount of gathered data and the relatively constant human ability to ingest information.
Visualization, as a methodology and tool of transforming complex data into an intuitive visual representation can leverage the combined computational resources and the human cognitive capabilities in order to mitigate this growing discrepancy.
A large portion of visualization research is, directly or indirectly, targets users in an application domain, such as medicine, biology, physics, or others.
Applied research is aimed at the creation of visualization applications or systems that solve a specific problem within the domain. Combining prior research and applying it to a concrete problem enables the possibility to compare and determine the usability and usefulness of existing visualization techniques.
These applications can only be effective when the domain experts are closely involved in the design process, leading to an iterative workflow that informs its form and function. These visualization solutions can be separated into three categories: Exploration, in which users perform an initial study of data, Analysis, in which an established technique is repeatedly applied to a large number of datasets, and Communication in which findings are published to a wider public audience.
For the finite element modeling, an exploration tool for simulations of stress tensors in a human heart uses a compression method to achieve interactive frame rates. In the medical domain, an analysis system aimed at guiding surgeons during Deep Brain Stimulation interventions fuses multiple modalities in order to improve their outcome.
For the astronomical domain, first, an exploration application enables the analysis of time-varying volumetric plasma simulations to improving these simulations and thus better predict space weather. A final system focusses on combining all three categories into a single application that enables the same tools to be used for Exploration, Analysis, and Communication, thus requiring the handling of large coordinate systems, and high-fidelity rendering of planetary surfaces and spacecraft operations.
This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses.
Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization.
Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on.
This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.
It reflects recent changes in educational practice through which text no longer occupies its traditionally dominant role as the prime means of presenting to-be-learned information to learners. Specifically, the book targets the dynamic visual components of multimedia educational resources and singles out how they can influence learning in their own right. It aims to help bridge the increasing gap between pervasive adoption of dynamic visualizations in educational practice and our limited understanding of the role that these representations can play in learning.
The volume has recruited international leaders in the field to provide diverse perspectives on the dynamic visualizations and learning. It is the first comprehensive book on the topic that brings together contributions from both renowned researchers and expert practitioners.
Rather than aiming to present a broad general overview of the field, it focuses on innovative work that is at the cutting edge. As well as further developing and complementing existing approaches, the contributions emphasize fresh ideas that may challenge existing orthodoxies and point towards future directions for the field.
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