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 visualization, Introduction to the theory of colour perception and the role of colour in conveying information about data, Comprehensive illustrations throughout, Exercises and problems to encourage further learning, Virtual laboratories available from Springer's website for those readers with access to the IRIS Explorer package.