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Consider a set of source schemas \({\mathcal {S}} = \{S_1, \dots , S_n\}\) in the same domain, where different schemas may describe the domain in different ways. An important component in data integration is schema alignment, including three steps: (1) creating a mediated schema M that provides a unified and virtual view of the disparate sources and captures the salient aspects of the domain being considered, (2) generating attribute matching that matches attributes in each source schema S i , i ∈ [1, n], to the corresponding attributes in the mediated schema M, and (3) building a schema mapping between each source schema S i and the mediated schema Mto specify the semantic relationships between the contents of the source and that of the mediated data. The result schema mappings are used to reformulate a user query into a set of queries on the underlying data sources for query answering. Uncertainty can arise in every step of schema...
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References
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Dong, X.L., Halevy, A. (2017). Managing Data Integration Uncertainty. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_80743-1
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DOI: https://doi.org/10.1007/978-1-4899-7993-3_80743-1
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