摘要
In web environments, proteomics data integra-tionin the life sciences needs to handle the problem of data conflicts arising from the het-erogeneity of data resources and from incom-patibilities between the inputs and outputs of services used in the analysis of the resources. The integration of complex, fast changing bio-logical data repositories can be potentially sup-ported by Grid computing to enable distributed data analysis. This paper presents an approach addressing the data conflict problems of pro-teomics data integration. We describe a pro-posed proteomics data integration architecture, in which a heterogeneous data integration sys-tem interoperates with Web Services and query processing tools for the virtual and materialised integration of a number of proteomics resources, either locally or remotely. Finally, we discuss how the architecture can be further used for supporting data maintenance and analysis ac-tivities.
In web environments, proteomics data integra-tionin the life sciences needs to handle the problem of data conflicts arising from the het-erogeneity of data resources and from incom-patibilities between the inputs and outputs of services used in the analysis of the resources. The integration of complex, fast changing bio-logical data repositories can be potentially sup-ported by Grid computing to enable distributed data analysis. This paper presents an approach addressing the data conflict problems of pro-teomics data integration. We describe a pro-posed proteomics data integration architecture, in which a heterogeneous data integration sys-tem interoperates with Web Services and query processing tools for the virtual and materialised integration of a number of proteomics resources, either locally or remotely. Finally, we discuss how the architecture can be further used for supporting data maintenance and analysis ac-tivities.
