Introduction to Scientific Visualization
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Beschreibung
Scientific visualization is recognised as important for understanding data, whether measured, sensed remotely or calculated. Introduction to Scientific Visualization is aimed at readers who are new to the subject, either students taking an advanced option at undergraduate level or postgraduates wishing to visualize some specific data.An introductory chapter on the philosophy of the subject sets the scene, showing why visualization works and what to aim for when presenting scientific data visually. Then, extending and applying Brodlie's taxonomy to underpin its core chapters, the book shows how to classify data, choose a technique that's appropriate for its visualization, and alerts readers to some of the pitfalls before they can invalidate their conclusions. The book concludes with an annotated bibliography and suggestions for further reading.Above all, this is a 'how to do it' book for scientific visualization, with:Discussion of the different types of software architecture for visualizationIntroduction to the theory of colour perception and the role of colour in conveying information about dataComprehensive illustrations throughoutExercises and problems to encourage further learningVirtual laboratories available from Springer’s website for those readers with access to the IRIS Explorer package Dr. Helen Wright is a Senior Lecturer in the Computer Science department at the University of Hull. She has many years experience teaching scientific visualization to undergraduates and postgraduates, and the material used in this book has been tested through successive taught courses.
This is a ‘how to’ book for scientific visualization. SciViz has not been covered in an approachable form (other than in compilations of research papers) since Brodlie’s seminal work "Scientific Visualization: Techniques and Applications" in 1992. This book does not treat the subject as a subset of information visualisation, but rather as a subject in its own right and the author uses a straightforward approach with a non-mathematical basis. An introduction on the philosophy of the subject sets the scene. The theory of colour perception and its value and use for conveying information about data is introduced. Next, using Brodlie’s taxonomy to underpin its core chapters, it is shown how to classify data. Worked examples are given throughout the text and there are practical ‘sidebars’ - virtual laboratory classes for those readers with access to the IRIS Explorer software who can try out the demonstrations on an accompanying website. The book concludes with a ‘taster’ of ongoing research.
The subject of scientific visualisation has primarily been covered in compilations of research papers, apart from Brodie's seminal work "Scientific Visualization Techniques and Applications" which was published in 1992. Dr Wright's book remedies this by providing a coherent and accessible approach to the subject which will be welcomed by readers. This book does not treat the subject as a subset of information visualisation, but rather as a subject in its own right Author uses straightforward language and uses a structured approach to the subject, with a non-mathematical basis. Includes supplementary material: sn.pub/extras Request lecturer material: sn.pub/lecturer-material
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Helen Wright
Themen in »Introduction to Scientific Visualization«
Computer Data Visualisation Scientific Visualization architecture computer science information visualization learning visualization
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From the reviews:
"Wright, after an overview of the field, presents the basics of color, provides an exemplary taxonomy of visualization techniques … . the book also contains a bibliography, references, solutions to exercises, a list of useful Web sites, common abbreviations, a glossary, and a comprehensive index. … all the visualization techniques are lucidly described, with clear … examples, corresponding charts, and color plates. … Readers looking for a short and accessible introduction to visualization techniques can’t go wrong with Wright’s book." (D. Spinellis, ACM Computing Reviews, September, 2008)
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