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Semantic Provenance for eScience: Managing the Deluge of Scientific Data

Provenance information in eScience is metadata that's critical to effectively manage the exponentially increasing volumes of scientific data from industrial-scale experiment protocols. Semantic provenance, based on domain-specific provenance ontologies, lets software applications unambiguously...

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Bibliographic Details
Published in:IEEE internet computing 2008-07, Vol.12 (4), p.46-54
Main Authors: Sahoo, S.S., Sheth, A., Henson, C.
Format: Article
Language:English
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Summary:Provenance information in eScience is metadata that's critical to effectively manage the exponentially increasing volumes of scientific data from industrial-scale experiment protocols. Semantic provenance, based on domain-specific provenance ontologies, lets software applications unambiguously interpret data in the correct context. The semantic provenance framework for eScience data comprises expressive provenance information and domain-specific provenance ontologies and applies this information to data management. The authors' "two degrees of separation" approach advocates the creation of high-quality provenance information using specialized services. In contrast to workflow engines generating provenance information as a core functionality, the specialized provenance services are integrated into a scientific workflow on demand. This article describes an implementation of the semantic provenance framework for glycoproteomics.
ISSN:1089-7801
1941-0131
DOI:10.1109/MIC.2008.86