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Modern Accelerator Technologies for Geographic Information Science pp 215–226Cite as

Pursuing Spatiotemporally Integrated Social Science Using Cyberinfrastructure

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Abstract

The rich details of space-time complexity in social science remain largely unexplored because of the challenge of intensities of data and computing. The current space-time simulation and statistics for social science research can only deal with a limited amount of data. We introduce a pilot study about how to deploy the modern accelerator technology and hybrid computer systems to extend the National Institute of Justice-funded Near-repeat calculation, a typical social science application? This pilot study demonstrates that it is promising to leverage high performance computing for solving large-scale space-time interaction problems, which has long been a challenging statistical issue for spatiotemporally integrated social science.

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Notes

  1. 1.

    The near-repeat calculator uses a simpler filtering technique. The near-repeat calculator filters out the shootings which are either not close in time or not close in space to the focal shooting.

  2. 2.

    This work was supported partially by the National Science Foundation through the award OCI-1047916.

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Author information

Authors and Affiliations

  1. Department of Geography, Kent State University, Kent, OH, 44242, USA

    Xinyue Ye

  2. Department of Geosciences, University of Arkansas, Fayetteville, AR, 72701, USA

    Xuan Shi

Authors
  1. Xinyue Ye
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  2. Xuan Shi
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Correspondence to Xinyue Ye .

Editor information

Editors and Affiliations

  1. Department of Geosciences, University of Arkansas, Fayetteville, Arkansas, USA

    Xuan Shi

  2. Department of Electrical and Computer Engineering, University of Illinois, Urbana, Illinois, USA

    Volodymyr Kindratenko

  3. Department of Geography and GeoInformation Sciences, George Mason University, Fairfax, Virginia, USA

    Chaowei Yang

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Ye, X., Shi, X. (2013). Pursuing Spatiotemporally Integrated Social Science Using Cyberinfrastructure. In: Shi, X., Kindratenko, V., Yang, C. (eds) Modern Accelerator Technologies for Geographic Information Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-8745-6_16

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  • DOI: https://doi.org/10.1007/978-1-4614-8745-6_16

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4614-8744-9

  • Online ISBN: 978-1-4614-8745-6

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