Semantic Web-Based Framework for Scientific Workflows in E-Science

Semantic Web-Based Framework for Scientific Workflows in E-Science

Singanamalla Vijayakumar (VIT University, India), Nagaraju Dasari (VIT University, India), Bharath Bhushan (VIT University, India) and Rajasekhar Reddy (VIT University, India)
DOI: 10.4018/978-1-5225-5191-1.ch018
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In the future generation, computer science plays prominent role in the scientific research. The development in the field of computers will leads to the research benefits of scientific community for sharing data, service computing, building the frameworks and many more. E-Science is the active extending field in the world by the increase data and tools. The proposed work discusses the use of semantic web applications for identifying the components in the development of scientific workflows. The main objective of the proposed work is to develop the framework which assists the scientific community to test and deploy the scientific experiments with the help of ontologies, service repositories, web services and scientific workflows. The framework which aims to sustenance the scientific results and management of applications related to the specific domain. The overall goal of this research is to automate the use of semantic web services, generate the workflows, manage the search services, manage the ontologies by considering the web service composition.
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Literature Review

The Voss A, et. al., 2008, author proposed an e-research model in which the resources are provided as services through dashboards with all operations that are essential. The end user can invoke the services through interface by submitting job.

The various scientific workflow management systems help in processing data, computing resources and as well as variety of applications. The popular workflow systems such as Kepler (Ludäscher B, et. al. 2005), Taverna (Oinn T, et. al., 2004), Triana (Taylor I, et. al., 2004), Pegasus (Deelman E, et. al., 2007), ASKALON (Fahringer T, et. al., 2005), SWIFT (Zhao Y, et. al., 2007) and Pipeline Pilot (Yang X, et. al., 2010). These work flow systems perform better in terms of usability, automation, efficiency and reproducibility.

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