Comparing models of computation
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Taverna: lessons in creating a workflow environment for the life sciences: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Scientific workflow management and the Kepler system: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Taverna Workflows: Syntax and Semantics
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
DFL: A dataflow language based on Petri nets and nested relational calculus
Information Systems
Towards a Formal Semantics for the Process Model of the Taverna Workbench. Part I
Fundamenta Informaticae
Petri net + nested relational calculus = dataflow
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
Collection-Oriented scientific workflows for integrating and analyzing biological data
DILS'06 Proceedings of the Third international conference on Data Integration in the Life Sciences
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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 second of two. In the first one [13] we have defined, explained and discussed fundamental notions for describing Scufl graphs and their semantics. Here, 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.