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Process Design for Natural Scientists pp 1–13Cite as

Scientific Workflows and XMDD

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 500))

Abstract

A major part of the scientific experiments that are carried out today requires thorough computational support. While database and algorithm providers face the problem of bundling resources to create and sustain powerful computation nodes, the users have to deal with combining sets of (remote) services into specific data analysis and transformation processes. Today’s attention to “big data” amplifies the issues of size, heterogeneity, and process-level diversity/integration. In the last decade, especially workflow-based approaches to deal with these processes have enjoyed great popularity. This book concerns a particularly agile and model-driven approach to manage scientific workflows that is based on the XMDD paradigm. In this chapter we explain the scope and purpose of the book, briefly describe the concepts and technologies of the XMDD paradigm, explain the principal differences to related approaches, and outline the structure of the book.

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Authors and Affiliations

  1. Service and Software Engineering, Potsdam University, Potsdam, D-14482, Germany

    Anna-Lena Lamprecht & Tiziana Margaria

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  1. Anna-Lena Lamprecht
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  2. Tiziana Margaria
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  1. Chair Service and Software Engineering, Institute of Computer Science, University of Potsdam, Potsdam, Germany

    Anna-Lena Lamprecht

  2. Chair Software Engineering, Computer Science and Information Systems Department, University of Limerick and Lero, The Irish Software Research Center, Limerick, Ireland

    Tiziana Margaria

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Lamprecht, AL., Margaria, T. (2014). Scientific Workflows and XMDD. In: Lamprecht, AL., Margaria, T. (eds) Process Design for Natural Scientists. Communications in Computer and Information Science, vol 500. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45006-2_1

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