Semantic Provenance for eScience: Managing the Deluge of Scientific Data Export

@article{citeulike:4926337, 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.}, author = {Sahoo, S. S. and Sheth, A. and Henson, C.}, booktitle = {Internet Computing, IEEE}, citeulike-article-id = {4926337}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/MIC.2008.86}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4557978}, doi = {10.1109/MIC.2008.86}, journal = {Internet Computing, IEEE}, keywords = {digital-earth}, number = {4}, pages = {46--54}, posted-at = {2009-06-22 21:45:17}, priority = {2}, title = {Semantic Provenance for eScience: Managing the Deluge of Scientific Data}, url = {http://dx.doi.org/10.1109/MIC.2008.86}, volume = {12}, year = {2008} }

TY - JOUR ID - citeulike:4926337 L3 - citeulike-article-id:4926337 N2 - 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. IS - 4 JF - Internet Computing, IEEE EP - 54 TI - Semantic Provenance for eScience: Managing the Deluge of Scientific Data VL - 12 T2 - Internet Computing, IEEE SP - 46 KW - digital-earth AU - Sahoo, SS AU - Sheth, A AU - Henson, C PY - 2008/// UR - http://dx.doi.org/10.1109/MIC.2008.86 ER -