首页> 外文会议>Grid and Cooperative Computing Workshops, 2006. GCCW '06. Fifth International Conference on >Ontology-Driven Composition and Validation of Scientific Grid Workflows in Kepler: a Case Study of Hyperspectral Image Processing
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Ontology-Driven Composition and Validation of Scientific Grid Workflows in Kepler: a Case Study of Hyperspectral Image Processing

机译:开普勒中本体驱动的组成和科学网格工作流的验证:以高光谱图像处理为例

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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
机译:由于高光谱图像的数据量大且处理需要大量计算,因此基于网格计算技术的高光谱图像处理具有吸引力。许多现有的网格工作流程工具不提供集成的可视工作流程组成环境和/或不具有工作流程验证机制来确保所组成的网格工作流程的结构和语义正确性。在这项研究中,我们使用开普勒科学工作流程系统来组成和验证高光谱图像处理网格工作流程,这是由于其集成的工作流程组成环境,对网格计算的丰富支持以及用于结构和语义工作流程验证的内置基础结构。我们已经开发了工作流组件本体和数据类型本体,并将它们插入开普勒。实验已经证明了该方法的可行性和有效性。

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