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International Conference on Scientific and Statistical Database Management

SSDBM 2011: Scientific and Statistical Database Management pp 253–254Cite as

A Panel Discussion on Data Intensive Science: Moving towards Solutions

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6809))

Abstract

Over the past several years, a number of groups, including the National Academy of Engineering, have identified grand challenge problems facing scientists from around the world [1]. While addressing these problems will have global impact, solutions are years away at best – and the next set of challenges are likely to be even harder to solve. Because of the complexity of questions being asked, meeting these challenges requires large, multi-disciplinary teams working closely together for extended periods of time. Enabling this new type of science, involving distributed teams that need to collaborate despite vastly different backgrounds and interests, is the cornerstone of Data Intensive Science.

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References

  1. National Academy of Engineering, “Grand Challenges for Engineering”, http://www.engineeringchallenges.org/cms/challenges.aspx

  2. Hey, A.J.G., Tansley, S., Tolle, K.M.: The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research (2009)

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  3. Shoshani, Rotem, D. (eds.): Scientific Data Management: Challenges, Technology, and Deployment. Chapman & Hall/CRC Computational Science Series (December 2009)

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Author information

Authors and Affiliations

  1. Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, WA, 99352, USA

    Terence Critchlow

Authors
  1. Terence Critchlow
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Editor information

Editors and Affiliations

  1. The Evergreen State College, 98505, Olympia, WA, USA

    Judith Bayard Cushing

  2. CNRI and University of Virginia, 22908, Charlottesville, VA, USA

    James French

  3. Gonzaga University, 99258, Spokane, WA, USA

    Shawn Bowers

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Critchlow, T. (2011). A Panel Discussion on Data Intensive Science: Moving towards Solutions. In: Bayard Cushing, J., French, J., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2011. Lecture Notes in Computer Science, vol 6809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22351-8_15

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  • DOI: https://doi.org/10.1007/978-3-642-22351-8_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22350-1

  • Online ISBN: 978-3-642-22351-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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