A declarative language and toolkit for scientific workflow implementation and execution

Abstract

Scientific workflow design is usually complex and demands access to and integration of numerous non-conventional resources. Geographical distribution and semantic heterogeneity of these resources add to this complexity. The cost effectiveness of such workflow design, thus, depends upon the lifespan of the application and its anticipated use. Shorter application lifespan usually entails prohibitive development costs. In this paper, we present an alternative platform for declarative workflow design using BioFlow in such environments. BioFlow is being developed as the query language for a scientific data management system called LifeDB that aims to support on-the-fly data integration and workflow support for life sciences applications. We argue that a declarative and ad hoc workflow design using BioFlow is more efficient and cost effective compared to traditional approaches using systems such as Taverna or Kepler. To demonstrate the advantages of BioFlow, we compare a canonical microarray data analysis workflow application design approach using BioFlow with Taverna and a gene regulation application using BioFlow and Kepler. We show that BioFlow supports ad hoc and modular application design at a throw away cost and produces a superior maintainable application that can adapt to changes in the source without significant effort compared to both Taverna and Kepler.