Actor-Oriented Design of Scientific Workflows
Scientific workflows are becoming increasingly important as a unifying mechanism for interlinking scientific data management, analysis, simulation, and visualization tasks. Scientific workflow systems are problem-solving environments, supporting scientists in the creation and execution of scientific workflows. While current systems permit the creation of executable workflows, conceptual modeling and design of scientific workflows has largely been neglected. Unlike business workflows, scientific workflows are typically highly data-centric naturally leading to dataflow-oriented modeling approaches. We first develop a formal model for scientific workflows based on an actor-oriented modeling and design approach, originally developed for studying models of complex concurrent systems. Actor-oriented modeling separates two modeling concerns: component communication (dataflow) and overall workflow coordination (orchestration). We then extend our framework by introducing a novel hybrid type system, separating further the concerns of conventional data modeling (structural data type) and conceptual modeling (semantic type). In our approach, semantic and structural mismatches can be handled independently or simultaneously, and via different types of adapters, giving rise to new methods of scientific workflow design.
KeywordsOutput Port Input Port Semantic Type Abstract Actor Composite Actor
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- 1.Ailamaki, A., Ioannidis, Y.E., Livny, M.: Scientific Workflow Management by Database Management. In: Proc. of SSDBM, pp. 190–199 (1998)Google Scholar
- 2.Alonso, G., Mohan, C.: Workflow Management Systems: The Next Generation of Distributed Processing Tools. In: Advanced Transaction Models and Architectures (1997)Google Scholar
- 3.Batini, C., Ceri, S., Navathe, S.: Conceptual Database Design: An Entity-Relationship Approach. Benjamin/Cummings (1992)Google Scholar
- 6.Castagna, G.: Covariance and contravariance: conflict without a cause. ACM Transactions on Programming Languages and Systems (TOPLAS) 17(3) (1995)Google Scholar
- 7.Wright, K.W.B.H., Brown, M.J.: The Dataflow Visualization Pipeline as a Problem Solving Environment. In: Virtual Environments and Scientific Visualization. Springer, Heidelberg (1996)Google Scholar
- 8.Kiepuszewski, B.: Expressiveness and Suitability of Languages for Control Flow Modelling in Workflows. Ph.D. Thesis, Queensland University of Technology (2002)Google Scholar
- 9.Lee, E.A., Neuendorffer, S.: Actor-oriented Models for Codesign: Balancing Re-Use and Performance. In: Formal Methods and Models for Systems. Kluwer, Dordrecht (2004)Google Scholar
- 11.Ludäscher, B., Altintas, I., Chad Berkley, D.H., Jaeger-Frank, E., Jones, M., Lee, E., Tao, J., Zhao, Y.: Scientific Workflow Management and the Kepler System. In: Concurrency and Computation: Practice and Experience, Special Issue on Scientific Workflows (2005) (to appear)Google Scholar
- 12.Majithia, S., Shields, M.S., Taylor, I.J., Wang, I.: Triana: A Graphical Web Service Composition and Execution Toolkit. In: Proc. of the IEEE Intl. Conf. on Web Services (ICWS). IEEE Computer Society, Los Alamitos (2004)Google Scholar
- 13.Meidanis, J., Vossen, G., Weske, M.: Using Workflow Management in DNA Sequencing. In: Proc. of CoopIS, pp. 114–123 (1996)Google Scholar
- 16.van der Aalst, W., van Hee, K.: Workflow Management: Models, Methods, and Systems (Cooperative Information Systems). MIT Press, Cambridge (2002)Google Scholar
- 18.zur Muehlen, M.: Workflow-based Process Controlling: Foundation, Design, and Application of workflow-driven Process Information Systems. Logos Verlag, Berlin (2004)Google Scholar