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Hybrid Storage Design for NC-94 Database Within the Parametric Data Model Framework

  • Conference paper
Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3981))

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Abstract

The NC-94 dataset contains the most complete records of temporal and spatial variables for climate, crop, and soil in the north central region in the United States. Scientists store and process the dataset within scientific data formats which are efficient for scientific simulations. However, it is difficult for the public to access the dataset by using ad-hoc queries because the scientific data formats are not database management systems. This paper presents a hybrid storage model to build the NC-94 database which supports ad-hoc queries. The storage is designed within the parametric data model which has advantages over conventional relational databases. In our design paradigm, the database query language supports multi-granules as well as pattern windows to extract information, reducing the needs of high-level programming languages. We expect that our proposed paradigm significantly enhance the usefulness of the existing NC-94 dataset for the public domain.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, Iowa State University, Ames, Iowa, 50010, USA

    Seo-Young Noh

Authors
  1. Seo-Young Noh
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Noh, SY. (2006). Hybrid Storage Design for NC-94 Database Within the Parametric Data Model Framework. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751588_16

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  • DOI: https://doi.org/10.1007/11751588_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34072-0

  • Online ISBN: 978-3-540-34074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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