Ontology-Driven Composition and Validation of Scientific Grid Workflows in Kepler: a Case Study of Hyperspectral Image Processing

Hyperspectral image processing based on grid computing technology is attractive due to the large data volumes of hyperspectral images and intensive computation requirements for processing. Many existing grid workflow tools do not provide integrated visual workflow composition environments and/or do not have workflow validation mechanisms to ensure structural and semantic correctness of composed grid workflows. In this study, we use Kepler scientific workflow system to compose and validate hyperspectral image processing grid workflows due to its integrated workflow composition environment, rich support for grid computing and built-in infrastructures for structural and semantic workflow validations. We have developed workflow component ontology and data type ontology and plugged them into Kepler. Experiments have been performed to demonstrate the feasibility and effectiveness of the proposed approach