Handbook of Human Centric Visualization


Book Description

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.




Human-Centered Data Science


Book Description

Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns.




Design of Visualizations for Human-Information Interaction


Book Description

Interest in visualization design has increased in recent years. While there is a large body of existing work from which visualization designers can draw, much of the past research has focused on developing new tools and techniques that are aimed at specific contexts. Less focus has been placed on developing holistic frameworks, models, and theories that can guide visualization design at a general level—a level that transcends domains, data types, users, and other contextual factors. In addition, little emphasis has been placed on the thinking processes of designers, including the concepts that designers use, while they are engaged in a visualization design activity. In this book we present a general, holistic framework that is intended to support visualization design for human-information interaction. The framework is composed of a number of conceptual elements that can aid in design thinking. The core of the framework is a pattern language—consisting of a set of 14 basic, abstract patterns—and a simple syntax for describing how the patterns are blended. We also present a design process, made up of four main stages, for creating static or interactive visualizations. The 4-stage design process places the patterns at the core of designers’ thinking, and employs a number of conceptual tools that help designers think systematically about creating visualizations based on the information they intend to represent. Although the framework can be used to design static visualizations for simple tasks, its real utility can be found when designing visualizations with interactive possibilities in mind—in other words, designing to support a human-information interactive discourse. This is especially true in contexts where interactive visualizations need to support complex tasks and activities involving large and complex information spaces. The framework is intended to be general and can thus be used to design visualizations for diverse domains, users, information spaces, and tasks in different fields such as business intelligence, health and medical informatics, digital libraries, journalism, education, scientific discovery, and others. Drawing from research in multiple disciplines, we introduce novel concepts and terms that can positively contribute to visualization design practice and education, and will hopefully stimulate further research in this area.




Visualizing Complexity


Book Description

How can you turn dry statistics into attractive and informative graphs? How can you present complex data sets in an easily understandable way? How can you create narrative diagrams from unstructured data? This handbook of information design answers these questions. Nicole Lachenmeier and Darjan Hil condense their extensive professional experience into an illustrated guide that offers a modular design system comprised of 80 elements. Their systematic design methodology makes it possible for anyone to visualize complex data attractively and using different perspectives. At the intersection of design, journalism, communication and data science, Visualizing Complexity opens up new ways of working with abstract data and invites readers to try their hands at information design.




Visualization Psychology


Book Description

This book designates Visualization Psychology as an interdisciplinary subject. The book contains literature reviews and experimental works that exemplify a range of open questions at this critical intersection. It also includes discourses that envision how the subject may be developed in the coming years and decades. The field of visualization is a rich playground for discovering new knowledge in both visualization and psychology. As visualization techniques augment human cognition, these techniques must be developed and improved by building on theoretical, empirical and methodological knowledge from psychology. At the same time, visualization processes surface numerous phenomena about interactions between the human mind and digital entities, such as data, visual imagery, algorithms, and computer-generated predictions and recommendations. Visualization psychology is a new type of science in the making.




Human Interface and the Management of Information: Information, Design and Interaction


Book Description

The two-volume set LNCS 9734 and 9735 constitutes the refereed proceedings of the Human Interface and the Management of Information thematic track, held as part of the 18th International Conference on Human-Computer Interaction, HCII 2016, held in Toronto, Canada, in July 2016. HCII 2016 received a total of 4354 submissions of which 1287 papers were accepted for publication after a careful reviewing process. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers accepted for presentation thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas This volume contains papers addressing the following major topics: information presentation; big data visualization; information analytics; discovery and exploration; interaction design, human-centered design; haptic, tactile and multimodal interaction.




User-Centered Evaluation of Visual Analytics


Book Description

Visual analytics has come a long way since its inception in 2005. The amount of data in the world today has increased significantly and experts in many domains are struggling to make sense of their data. Visual analytics is helping them conduct their analyses. While software developers have worked for many years to develop software that helps users do their tasks, this task is becoming more and more onerous, as understanding the needs and data used by expert users requires more than some simple usability testing during the development process. The need for a user-centered evaluation process was envisioned in Illuminating the Path, the seminal work on visual analytics by James Thomas and Kristin Cook in 2005. We have learned over the intervening years that not only will user-centered evaluation help software developers to turn out products that have more utility, the evaluation efforts can also help point out the direction for future research efforts. This book describes the efforts that go into analysis, including critical thinking, sensemaking, and various analytics techniques learned from the intelligence community. Support for these components is needed in order to provide the most utility for the expert users. There are a good number of techniques for evaluating software that hasbeen developed within the human-computer interaction (HCI) community. While some of these techniques can be used as is, others require modifications. These too are described in the book. An essential point to stress is that the users of the domains for which visual analytics tools are being designed need to be involved in the process. The work they do and the obstacles in their current processes need to be understood in order to determine both the types of evaluations needed and the metrics to use in these evaluations. At this point in time, very few published efforts describe more than informal evaluations. The purpose of this book is to help readers understand the need for more user-centered evaluations to drive both better-designed products and to define areas for future research. Hopefully readers will view this work as an exciting and creative effort and will join the community involved in these efforts.




The Routledge Handbook of Mapping and Cartography


Book Description

This new Handbook unites cartographic theory and praxis with the principles of cartographic design and their application. It offers a critical appraisal of the current state of the art, science, and technology of map-making in a convenient and well-illustrated guide that will appeal to an international and multi-disciplinary audience. No single-volume work in the field is comparable in terms of its accessibility, currency, and scope. The Routledge Handbook of Mapping and Cartography draws on the wealth of new scholarship and practice in this emerging field, from the latest conceptual developments in mapping and advances in map-making technology to reflections on the role of maps in society. It brings together 43 engaging chapters on a diverse range of topics, including the history of cartography, map use and user issues, cartographic design, remote sensing, volunteered geographic information (VGI), and map art. The title’s expert contributions are drawn from an international base of influential academics and leading practitioners, with a view to informing theoretical development and best practice. This new volume will provide the reader with an exceptionally wide-ranging introduction to mapping and cartography and aim to inspire further engagement within this dynamic and exciting field. The Routledge Handbook of Mapping and Cartography offers a unique reference point that will be of great interest and practical use to all map-makers and students of geographic information science, geography, cultural studies, and a range of related disciplines.




Visualization of Time-Oriented Data


Book Description

This is an open access book. Time is an exceptional dimension with high relevance in medicine, engineering, business, science, biography, history, planning, or project management. Understanding time-oriented data via visual representations enables us to learn from the past in order to predict, plan, and build the future. This second edition builds upon the great success of the first edition. It maintains a brief introduction to visualization and a review of historical time-oriented visual representations. At its core, the book develops a systematic view of the visualization of time-oriented data. Separate chapters discuss interaction techniques and computational methods for supporting the visual data analysis. Many examples and figures illustrate the introduced concepts and techniques. So, what is new for the second edition? First of all, the second edition is now published as an open-access book so that anyone interested in the visualization of time and time-oriented data can read it. Second, the entire content has been revised and expanded to represent state-of-the-art knowledge. The chapter on interaction support now includes advanced methods for interacting with visual representations of time-oriented data. The second edition also covers the topics of data quality as well as segmentation and labeling. The comprehensive survey of classic and contemporary visualization techniques now provides more than 150 self-contained descriptions accompanied by illustrations and corresponding references. A completely new chapter describes how the structured survey can be used for the guided selection of suitable visualization techniques. For the second edition, our TimeViz Browser, the digital pendant to the survey of visualization techniques, received a major upgrade. It includes the same set of techniques as the book, but comes with additional filter and search facilities allowing scientists and practitioners to find exactly the solutions they are interested in.




Foundations of Data Visualization


Book Description

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.