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

How should we understand and visualise the uncertainty inherent in decision-making? Using the right visualisation tools can improve our decisions. But this positive impact should never be taken for granted: visualisations can also have unexpected side-effects, and there is the risk that they can be misinterpreted or otherwise misused.

II Challenges in Data Mapping Part II deals with one of the most challenging tasks in Interactive Visualization, mapping and teasing out information from large complex datasets and generating visual representations. This section consists of four chapters. Binh Pham, Alex Streit, and Ross Brown provide a comprehensive requirement analysis of information uncertainty visualizations. They examine the sources of uncertainty, review aspects of its complexity, introduce typical models of uncertainty, and analyze major issues in visualization of uncertainty, from various user and task perspectives. Alfred Inselberg examines challenges in the multivariate data analysis. He explains how relations among multiple variables can be mapped uniquely into ?-space subsets having geometrical properties and introduces Parallel Coordinates meth- ology for the unambiguous visualization and exploration of a multidimensional geometry and multivariate relations. Christiaan Gribble describes two alternative approaches to interactive particle visualization: one targeting desktop systems equipped with programmable graphics hardware and the other targeting moderately sized multicore systems using pack- based ray tracing. Finally, Christof Rezk Salama reviews state-of-the-art strategies for the assignment of visual parameters in scientific visualization systems. He explains the process of mapping abstract data values into visual based on transfer functions, clarifies the terms of pre- and postclassification, and introduces the state-of-the-art user int- faces for the design of transfer functions.

This book highlights advances in Cyber Security, Cyber Situational Awareness (CyberSA), Artificial Intelligence (AI) and Social Media. It brings together original discussions, ideas, concepts and outcomes from research and innovation from multidisciplinary experts. It offers topical, timely and emerging original innovations and research results in cyber situational awareness, security analytics, cyber physical systems, blockchain technologies, machine learning, social media and wearables, protection of online digital service, cyber incident response, containment, control, and countermeasures (CIRC3). The theme of Cyber Science 2022 is Ethical and Responsible use of AI. Includes original contributions advancing research in Artificial Intelligence, Machine Learning, Blockchain, Cyber Security, Social Media, Cyber Incident Response & Cyber Insurance. Chapters “Municipal Cybersecurity—A Neglected Research Area? A Survey of Current Research", "The Transnational Dimension of Cybersecurity: The NIS Directive and its Jurisdictional Challenges" and "Refining the Mandatory Cybersecurity Incident Reporting under the NIS Directive 2.0: Event Types and Reporting Processes” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This two-volume set LNCS 13305 - 13306 constitutes the thoroughly refereed proceedings of the thematic area Human Interface and the Management of Information, HIMI 2022, which was held as part of HCI International 2022 and took place virtually during June 26-July 1, 2022. The total of 1271 papers and 275 poster papers included in the 39 HCII 2022 proceedings volumes was carefully reviewed and selected from 5487 submissions. The papers included in the HCII-HIMI volume set were organized in topical sections as follows: Part I: Human-centered design approaches; information design and quality; visual design; visualization and big data; Information, cognition and learning. Part II: Recommender systems; robots and avatars appearance and embodiment; information in virtual and augmented reality; information in complex technological environments.

This beautifully illustrated book is the first complete handbook to visual information. Well written, easy to use, and carefully indexed, it describes the full range of charts, graphs, maps, diagrams, and tables used daily to manage, analyze, and communicate information. It features over 3,000 illustrations, making it an ideal source for ideas on how to present information. It is an invaluable tool for anyone who writes or designs reports, whether for scientific journals, annual reports, or magazines and newspapers.

Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. • Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation, • Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets, • Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications, • Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms. Scientific Visualization will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics, and those interested in knowing more about the visualization process.