Distributed and Parallel Databases
Triana: A Graphical Web Service Composition and Execution Toolkit
ICWS '04 Proceedings of the IEEE International Conference on Web Services
Scientific workflow management and the Kepler system: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Flexible and Efficient Workflow Deployment of Data-Intensive Applications On Grids With MOTEUR
International Journal of High Performance Computing Applications
Workflows and e-Science: An overview of workflow system features and capabilities
Future Generation Computer Systems
Towards scientific workflow patterns
Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science
A multi-dimensional classification model for scientific workflow characteristics
Proceedings of the 1st International Workshop on Workflow Approaches to New Data-centric Science
Design and analysis of data management in scalable parallel scripting
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
A Grid-Enabled Gateway for Biomedical Data Analysis
Journal of Grid Computing
Common motifs in scientific workflows: An empirical analysis
E-SCIENCE '12 Proceedings of the 2012 IEEE 8th International Conference on E-Science (e-Science)
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Scientific workflow management is heavily used in our organization. After six years, a large number of workflows are available and regularly used to run biomedical data analysis experiments on distributed infrastructures, mostly on grids. In this paper we present our first efforts to better understand and characterise these workflows. We start with a set of considerations previously proposed in the literature (workflow dimensions and motifs), and revise these to more closely describe what we observe in our workflows. We conclude that workflow characteristics can be categorized at two levels: firstly, the features characterizing the distributed application and how to implement it as a workflow, and secondly, workflow motifs that depend on the features of the selected workflow management system. These characteristics could be useful in the future to understand a larger set of workflows and to identify functional requirements for further development workflow management systems.