In this technological age, we live in a sea of information. We face the problem of gleaning useful knowledge from masses of words and numbers stored in computers. Fortunately, the computing technology that produces this deluge also gives us some tools to transform heterogeneous information into knowledge. We now rely on computers at every stage of this transformation: structuring and exploring information, developing models, and communicating knowledge.
In this book we teach a methodology that makes visualization central to the process of abstracting knowledge from information. Computers give us great power to represent information in pictures, but even more, they give us the power to interact with these pictures. If these are pictures of data, then interaction gives us the feeling of having our hands on the data itself and helps us to orient ourselves in the sea of information. By generating and manipulating many pictures, we make comparisons among different views of the data, we pose queries about the data and get immediate answers, and we discover large patterns and small features of interest. These are essential facets of data exploration, and they are important for model development and diagnosis. In this first chapter we sketch the history of computer-aided data visualization and the role of data visualization in the process of data analysis.
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© 2007 Springer Science+Business Media, LLC
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(2007). Introduction. In: Interactive and Dynamic Graphics for Data Analysis. Use R!. Springer, New York, NY. https://doi.org/10.1007/978-0-387-71762-3_1
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DOI: https://doi.org/10.1007/978-0-387-71762-3_1
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-71761-6
Online ISBN: 978-0-387-71762-3
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