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Structure Discovery from Massive Spatial Data Sets Using Intelligent Simulation Tools

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Computational Discovery of Scientific Knowledge

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4660))

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Abstract

Extracting structures as communicable knowledge is a central problem in spatio-temporal data analysis. Spatial Aggregation is an effective way for discovering structures. To address the computational challenges posed by applications such as weather data analysis or engineering optimization, Spatial Aggregation recursively aggregates local data into higher-level descriptions, exploiting the fact that these physical phenomena can be described as spatio-temporally coherent “objects” due to continuity and locality in the underlying physics. This paper uses several problem domains — weather data interpretation, distributed control optimization, and spatio-temporal diffusion-reaction pattern analysis — to demonstrate that intelligent simulation tools built upon the principles of Spatial Aggregation are indispensable for scientific discovery and engineering analysis.

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Author information

Authors and Affiliations

  1. Palo Alto Research Center (PARC), Palo Alto, California, USA

    Feng Zhao

  2. Department of Computer Sciences, Purdue University, West Lafayette, Indiana, USA

    Chris Bailey-Kellogg

  3. The Ohio State University, Columbus, Ohio, USA

    Xingang Huang

  4. Bios Group, Santa Fe, New Mexico, USA

    Iván Ordóñez

Authors
  1. Feng Zhao
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  2. Chris Bailey-Kellogg
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  3. Xingang Huang
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  4. Iván Ordóñez
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Sašo Džeroski Ljupčo Todorovski

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© 2007 Springer-Verlag Berlin Heidelberg

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Zhao, F., Bailey-Kellogg, C., Huang, X., Ordóñez, I. (2007). Structure Discovery from Massive Spatial Data Sets Using Intelligent Simulation Tools. In: Džeroski, S., Todorovski, L. (eds) Computational Discovery of Scientific Knowledge. Lecture Notes in Computer Science(), vol 4660. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73920-3_8

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  • DOI: https://doi.org/10.1007/978-3-540-73920-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73919-7

  • Online ISBN: 978-3-540-73920-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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