Date Added: Mar 2012
Data-centric and service-oriented workflows are commonly used in scientific research to enable the composition and execution of complex analysis on distributed resources. Although there are a plethora of orchestration frameworks to implement workflows, most of them are not suitable to execute data-centric workflows. The main issue is transferring output of service invocations through a centralized orchestration engine to the next service in the workflow, which can be a bottleneck for the performance of a data-centric workflow. In this paper, the authors propose a flexible and lightweight workflow framework based on the Object Modeling Systems (OMS).