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    • Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

    Achim Streit, Jörg Meyer, Christopher Jung (eds.)

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    The Helmholtz Association funded the "Large-Scale Data Management and Analysis" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities.

    Umfang: V, 259 S.

    Preis: €46.00 | £42.00 | $81.00

    Fächer:

    Informatik und Mathematik 

    Schlagwörter:

    Big Data Data Science Datenlebenszyklus Datenmanagement Datenanalyse data science data life cycle data management data analysis

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    Empfohlene Zitierweise
    Streit, A et al. (eds.) 2017. Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000071931
    Streit, A., Meyer, J. and Jung, C., 2017. Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000071931
    Streit, A, et al.. Helmholtz Portfolio Theme Large-scale Data Management and Analysis (LSDMA). KIT Scientific Publishing, 2017. DOI: https://doi.org/10.5445/KSP/1000071931
    Streit, A., Meyer, J., & Jung, C. (2017). Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000071931
    Streit, Achim, Jörg Meyer, and Christopher Jung. 2017. Helmholtz Portfolio Theme Large-scale Data Management and Analysis (LSDMA). Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000071931



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    Weitere Informationen

    Veröffentlicht am 20. September 2017

    Sprache

    Englisch

    Seitenanzahl:

    276

    ISBN
    Paperback 978-3-7315-0695-9

    DOI
    https://doi.org/10.5445/KSP/1000071931