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Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration pp 285–302Cite as

Massive Data Visualization: A Survey

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Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Summary

Today’s scientific and engineering problems require a different approach to address the massive data problems in organization, storage, transmission, visualization, ex- ploration, and analysis. Visual techniques for data exploration are now common in many scientific, engineering, and business applications. However, the massive amount of data collected through simulation, collection and logging is inhibiting the use of conventional vi- sualization methods. We need to discover new visualization methods that allow us to explore the massive multidimensional time-varying information streams and turn overwhelming tasks into opportunities for discovery and analysis.

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Authors and Affiliations

  1. Institute for Data Analysis and Visualization, University of California, Davis

    Kenneth I. Joy

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  1. Kenneth I. Joy
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Editors and Affiliations

  1. School of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada

    Torsten Möller  & Robert D. Russell  & 

  2. Department of Computer Science, University of California, Davis, 1 Shields Avenue, Davis, CA, 95616-8562, USA

    Bernd Hamann

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Joy, K.I. (2009). Massive Data Visualization: A Survey. In: Möller, T., Hamann, B., Russell, R.D. (eds) Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/b106657_15

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