Semantic Provenance for eScience: Managing the Deluge of Scientific Data

Authors:
Satya S. Sahoo;Amit Sheth;Cory Henson
Affiliations:
Kno.e.sis Center, Wright State University;Kno.e.sis Center, Wright State University;Kno.e.sis Center, Wright State University
Venue:
IEEE Internet Computing
Year:
2008

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Abstract

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.