Omnispective analysis and reasoning

Scientific workflows are extensively used to support the management of experimental and computational research by connecting together different data sources, components and processes. However, certain issues such as the ability to check the appropriateness of the processes orchestrated, management of the context of workflow components and specification, and provision for robust management of intellectual concerns are not addressed adequately. Hence, it is highly desirable to add features to uplift focus from low level details to help clarify the rationale and intent behind the choices and decisions in the workflow specifications and provide a suitable level of abstraction to capture and organize intellectual concerns and map them to the workflow specification and execution semantics. In this paper, we present Omnispective Analysis and Reasoning (OAR), a novel framework for providing the above features and enhancements in scientific workflow management systems and processes. The OAR framework is aimed at supporting effective capture and reuse of intellectual concerns in workflow management.