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A Multidisciplinary, Model-Driven, Distributed Science Data System Architecture

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Guide to e-Science

Part of the book series: Computer Communications and Networks ((CCN))

Abstract

The twenty-first century has transformed the world of science by breaking the physical boundaries of distributed organizations and interconnecting them into virtual science environments, allowing for systems and systems of systems to seamlessly access and share information and resources across highly geographically distributed areas. This e-science transformation is enabling new scientific discoveries by allowing for greater collaboration as well as by enabling systems to combine and correlate disparate data sets. At the Jet Propulsion Laboratory in Pasadena, California, we have been developing science data systems for highly distributed communities in physical and life sciences that require extensive sharing of distributed services and common information models based on common architectures. The common architecture contributes a set of atomic functions, interfaces, and information models that support sharing and distributed processing. Additionally, the architecture provides a blueprint for a software product line known as the Object Oriented Data Technology (OODT) framework. OODT has enabled reuse of software for science data generation, capture and management, and delivery across highly distributed organizations for planetary science, earth science, and cancer research. Our experience to date shows that a well-defined architecture and set of accompanied software vastly improves our ability to develop road maps for and to construct virtual science environments.

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Notes

  1. 1.

     http://smc-it.org/workshops/crichton.html

  2. 2.

     http://www.ipcc.ch/workshops-experts-meetings-ar5-scoping.htm

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Acknowledgment

The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

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Authors and Affiliations

  1. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA

    Daniel J. Crichton, Chris A. Mattmann, John S. Hughes, Sean C. Kelly & Andrew F. Hart

  2. Computer Science Department, University of Southern California, Los Angeles, CA, 90089, USA

    Chris A. Mattmann

Authors
  1. Daniel J. Crichton
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  2. Chris A. Mattmann
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  3. John S. Hughes
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  4. Sean C. Kelly
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  5. Andrew F. Hart
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Corresponding author

Correspondence to Daniel J. Crichton .

Editor information

Editors and Affiliations

  1. Reading e-Science Centre, Harry Pitt Building, University of Reading, Earley Gate, Whiteknights 3, Reading, RG6 6AL, United Kingdom

    Xiaoyu Yang

  2. Pervasive Technology Institute, Indiana University, East 10th Street 2719, Bloomington, 47408, Indiana, USA

    Lizhe Wang

  3. Fac. Professional Studies, School of Computing, Thames Valley University, St. Mary's Road TC372, Ealing, London, W5 5RF, United Kingdom

    Wei Jie

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Crichton, D.J., Mattmann, C.A., Hughes, J.S., Kelly, S.C., Hart, A.F. (2011). A Multidisciplinary, Model-Driven, Distributed Science Data System Architecture. In: Yang, X., Wang, L., Jie, W. (eds) Guide to e-Science. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-0-85729-439-5_5

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  • DOI: https://doi.org/10.1007/978-0-85729-439-5_5

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