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Empowering Web Service Search with Business Know-How: Application to Scientific Workflows

Empowering Web Service Search with Business Know-How: Application to Scientific Workflows

Isabelle Mirbel, Pierre Crescenzo, Nadia Cerezo
Copyright: © 2011 |Pages: 16
ISBN13: 9781609605094|ISBN10: 1609605098|EISBN13: 9781609605100
DOI: 10.4018/978-1-60960-509-4.ch009
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MLA

Mirbel, Isabelle, et al. "Empowering Web Service Search with Business Know-How: Application to Scientific Workflows." Knowledge Engineering for Software Development Life Cycles: Support Technologies and Applications, edited by Muthu Ramachandran, IGI Global, 2011, pp. 161-176. https://doi.org/10.4018/978-1-60960-509-4.ch009

APA

Mirbel, I., Crescenzo, P., & Cerezo, N. (2011). Empowering Web Service Search with Business Know-How: Application to Scientific Workflows. In M. Ramachandran (Ed.), Knowledge Engineering for Software Development Life Cycles: Support Technologies and Applications (pp. 161-176). IGI Global. https://doi.org/10.4018/978-1-60960-509-4.ch009

Chicago

Mirbel, Isabelle, Pierre Crescenzo, and Nadia Cerezo. "Empowering Web Service Search with Business Know-How: Application to Scientific Workflows." In Knowledge Engineering for Software Development Life Cycles: Support Technologies and Applications, edited by Muthu Ramachandran, 161-176. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-509-4.ch009

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Abstract

Scientists who are not proficient in computer science and yet wish to perform in-silico experiments and harness the power of Service Oriented Architecture are presented with dozens of daunting technical solutions: scientific workflow frameworks. While these systems do take care of complex technical aspects such as Grid technologies, little is done to support transfer of service composition knowledge and know-how. The authors of this chapter believe the problem lies in the scientific workflow models which are too low-level and too anchored in the underlying technologies to allow efficient reuse and sharing. This chapter’s approach, called SATIS, relies on a goal-driven model, that has proven its worth in requirement engineering, and the Semantic Web technologies to leverage the collective knowledge and know-how in order to bridge the gap between service providers and end-users.

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