Subtyping can have a simple semantics
Theoretical Computer Science
Querying and Splicing of XML Workflows
CooplS '01 Proceedings of the 9th International Conference on Cooperative Information Systems
Building web services for scientific grid applications
IBM Journal of Research and Development
Taverna: lessons in creating a workflow environment for the life sciences: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
EMBRACE: Bioinformatics Data and Analysis Tool Services for e-Science
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
myExperiment: social networking for workflow-using e-scientists
Proceedings of the 2nd workshop on Workflows in support of large-scale science
Taverna Workflows: Syntax and Semantics
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
Implementation of Turing Machines with the Scufl Data-Flow Language
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
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Workflow development and enactment workbenches are becoming a standard tool for conducting in silico experiments. Their main advantages are easy to operate user interfaces, specialized and expressive graphical workflow specification languages and integration with a huge number of bioinformatic services. A popular example of such a workbench is Taverna, which has many additional useful features like service discovery, storing intermediate results and tracking data provenance. We discuss a detailed formal semantics for Scufl - the workflow definition language of the Taverna workbench. It has several interesting features that are notmet in other models including dynamic and transparent type coercion and implicit iteration, control edges, failure mechanisms, and incominglinks strategies. We study these features and investigate their usefulness separately as well as in combination, and discuss alternatives. The formal definition of such a detailed semantics not only allows to exactly understand what is being done in a given experiment, but is also the first step toward automatic correctness verification and allows the creation of auxiliary tools that would detect potential errors and suggest possible solutions to workflow creators, the same way as Integrated Development Environments aid modern programmers. A formal semantics is also essential for work on enactment optimization and in designing the means to effectively query workflow repositories. This paper is the first of two. It defines, explains and discusses fundamental notions for describing Scufl graphs and their semantics. Then, in the second part, we use these notions to define the semantics and show that our definition can be used to prove properties of Scufl graphs.