Adept_flex—Supporting Dynamic Changes of Workflows Without Losing Control
Journal of Intelligent Information Systems - Special issue on workflow management systems
Data & Knowledge Engineering - Special issue on ER '96
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Information Systems - Special issue on meta-modelling and methodology engineering
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Production workflow: concepts and techniques
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Data & Knowledge Engineering - Special issue: Advances in business process management
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ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
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ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
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ICSOC-ServiceWave '09 Proceedings of the 7th International Joint Conference on Service-Oriented Computing
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CAiSE'07 Proceedings of the 19th international conference on Advanced information systems engineering
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ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
ESCIENCE '10 Proceedings of the 2010 IEEE Sixth International Conference on e-Science
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BPM'11 Proceedings of the 9th international conference on Business process management
ServiceWave'11 Proceedings of the 4th European conference on Towards a service-based internet
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ICSOC'05 Proceedings of the Third international conference on Service-Oriented Computing
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IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
Enabling Flexibility in Process-Aware Information Systems: Challenges, Methods, Technologies
Enabling Flexibility in Process-Aware Information Systems: Challenges, Methods, Technologies
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Most of the existing scientific workflow systems rely on proprietary concepts and workflow languages. We are convinced that the conventional workflow technology that is established in business scenarios for years is also beneficial for scientists and scientific applications. We are therefore working on a scientific workflow system based on business workflow concepts and technologies. The system offers advanced flexibility features to scientists in order to support them in creating workflows in an explorative manner and to increase robustness of scientific applications. We named the approach Model-as-you-go because it enables users to model and execute workflows in an iterative process that eventually results in a complete scientific workflow. In this paper, we present main ingredients of Model-as-you-go, show how existing workflow concepts have to be extended in order to cover the requirements of scientists, discuss the application of the concepts to BPEL, and introduce the current prototype of the system.