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ABSTRACT
In recent years, scientists are dealing more and more with data intensive and complex applications. Many scientific workflow systems emerged which adapt technology and methods stemming from the workflow management area and that should support scientists in understanding and working with their complex scenarios. However as these systems often descend from problem solving environments, many of them are missing a well structured conceptual method for process modeling and execution as a foundation. In this publication we present a comprehensive and well structured method for developing and analyzing process based scientific applications. This method is constituted by a process modeling framework, a data integration framework and a model driven approach to build up infrastructures for process modeling and execution.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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