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A Methodology for Integration of Heterogeneous Databases
December 1994 (vol. 6 no. 6)
pp. 920-933

The transformation of existing local databases to meet diverse application needs at the global level is performed through a four-layered procedure that stresses total schema integration and virtual integration of local databases. The proposed methodology covers both schema integration and database integration, and uses a four-layered schema architecture (local schemata, local object schemata, global schema, and global view schemata) with each layer presenting an integrated view of the concepts that characterize the layer below. Mechanisms for accomplishing this objective are presented in theoretical terms, along with a running example. Object equivalence classes, property equivalence classes, and other related concepts are discussed in the context of logical integration of heterogeneous schemata, while object instance equivalence classes and property instance equivalence classes, and other related concepts are discussed for data integration purposes. The proposed methodology resolves naming conflicts, scaling conflicts, type conflicts, and level of abstraction, and other types of conflicts during schema integration, and data inconsistencies during data integration.

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Index Terms:
database management systems; equivalence classes; naming services; heterogeneous database integration methodology; local databases; diverse global application needs; total schema integration; virtual integration; 4-layered schema architecture; local schemata; local object schemata; global schema; global view schemata; object equivalence classes; property equivalence classes; logical integration; heterogeneous schemata; object instance equivalence classes; property instance equivalence classes; data integration; naming conflicts; scaling conflicts; type conflicts; abstraction level conflicts; data inconsistencies
M.P. Reddy, B.E. Prasad, P.G. Reddy, "A Methodology for Integration of Heterogeneous Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 6, no. 6, pp. 920-933, Dec. 1994, doi:10.1109/69.334882
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