One of the greatest scientific challenges of the 21st century is how to master, organize and extract useful knowledge from the overwhelming flow of information made available by today’s data acquisition systems and computing resources. Visualization is the premium means of taking up this challenge. This book is based on selected lectures given by leading experts in scientific visualization during a workshop held at Schloss Dagstuhl, Germany. Topics include user issues in visualization, large data visualization, unstructured mesh processing for visualization, volumetric visualization, flow visualization, medical visualization and visualization systems. The book contains more than 350 color illustrations.

Scientific visualization has always been an integral part of discovery, starting first with simplified drawings of the pre-Enlightenment and progressing to present day. Mathematical formalism often supersedes visual methods, but their use is at the core of the mental process. As historical examples, a spatial description of flow led to electromagnetic theory, and without visualization of crystals, structural chemistry would not exist. With the advent of computer graphics technology, visualization has become a driving force in modern computing. A Concise Introduction to Scientific Visualization – Past, Present, and Future serves as a primer to visualization without assuming prior knowledge. It discusses both the history of visualization in scientific endeavour, and how scientific visualization is currently shaping the progress of science as a multi-disciplinary domain.

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.

Numerical simulations of global warming, Mars observation data, and aircraft design are but a few of the topics where the use of human visual perception for data understanding are considered essential. Ten years agoa handful of pioneers professed the value of visualization to skeptical audiences. Today, with supercomputers and sensors producing ever-increasing amounts of data, scientific visualization is accepted throughout much of science and engineering as the fundamental tool for data analysis. Written by a world-wide panel of visualization experts, Scientific Visualization: Advances and Challenges presents astute coverage of prevailing trends, issues, and practice of scientific visualization. From algorithmic topics such as volume graphics and the modeling and visualization of large data sets, to foundations, perception, and interface technology (including virtual reality), this book provides the latest advances in the area. The book demonstrates new techniques, examines diverse application areas, and discusses current limitations and upcoming requirements. Scientific Visualization:Advances and Challenges $> presents readers with a unique opportunity to examine expert thinking and current practice, and to obtain a vision of potential future directions. It will be essential reading for scientific and engineering practitioners and visualization researchers alike. Offers extremely topical and timely coverage of a rapidly evolving area Includes contributions from an international panel of visualization experts in one accessible volume Provides scientific and engineering practitioners as well as visualization researchers with an essential guide to the literature

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.

This text surveys research from the fields of data mining and information visualisation and presents a case for techniques by which information visualisation can be used to uncover real knowledge hidden away in large databases.

Effective communication within learning environments is a pivotal aspect to students’ success. By enhancing abstract concepts with visual media, students can achieve a higher level of retention and better understand the presented information. Knowledge Visualization and Visual Literacy in Science Education is an authoritative reference source for the latest scholarly research on the implementation of visual images, aids, and graphics in classroom settings and focuses on how these methods stimulate critical thinking in students. Highlighting concepts relating to cognition, communication, and computing, this book is ideally designed for researchers, instructors, academicians, and students.