Classifying schematic and data heterogeneity in multidatabase systems

Kim, W.; Seo, Jungmin

doi:10.1109/2.116884

Cited by 293 publications

(149 citation statements)

References 7 publications

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“…We presented in this paper a model for schematic correspondences that extends and enriches those proposed by Kim et al [12]. The model proposed outperforms existing correspondence models in that it covers the information necessary to cater for automatic derivation of schema mappings.…”

Section: Discussionmentioning

confidence: 92%

“…In this paper, we show that the views implementing the mappings can be automatically derived if the correspondences defined by Kim et al [12] are refined in a number of carefully targeted ways. In essence, it is the argument of this paper that the classical approach to correspondence identification followed by (manual) mapping generation can be made more cost-effective through the removal of the second step based on judicious refinement of the correspondences captured.…”

Section: Introductionmentioning

confidence: 94%

“…Therefore, the elements connected by schematic correspondences are relations and/or attributes. As mentioned earlier, the model of schematic correspondences presented in this paper is built on the classification proposed by Kim et al [12]. This classification identifies a wide range of correspondences that may occur between two schemas.…”

Section: Schematic Correspondencesmentioning

confidence: 99%

“…For example, correspondences can be used to relate one element of a given schema to one element of another schema, e.g., Sint .Staff , S1 .Employee , or to relate multiple elements of one schema to one element of another schema, e.g., the correspondence Sint .Staff , {S1 .Employee, S1 .Department} states that the relation Staff in the integration schema is semantically equivalent to some combination of the relations Employee and Department of the source schema S 1 . There are several models for drawing schematic correspondences in the literature [17,7,14,12], of which the model proposed by Kim et al [12] is perhaps the most comprehensive. In the second phase of mapping specification, the views that implement the mappings necessary for rewriting the queries issued against the integration schema into queries over the schemas of the sources are specified.…”

Section: Introductionmentioning

confidence: 99%

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Defining and Using Schematic Correspondences for Automatically Generating Schema Mappings

Belhajjame

Paton

et al. 2009

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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Abstract. Mapping specification has been recognised as a critical bottleneck to the large scale deployment of data integration systems. A mapping is a description using which data structured under one schema are transformed into data structured under a different schema, and is central to data integration and data exchange systems. In this paper, we argue that the classical approach of correspondence identification followed by (manual) mapping generation can be simplified through the removal of the second step by judicious refinement of the correspondences captured. As a step in this direction, we present in this paper a model for schematic correspondences that builds on and extends the classification proposed by Kim et al. to cater for the automatic derivation of mappings, and present an algorithm that shows how correspondences specified in the model proposed can be used for deriving schema mappings. The approach is illustrated using a case study from integration in proteomics.

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Section: Discussionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 94%

Section: Schematic Correspondencesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Defining and Using Schematic Correspondences for Automatically Generating Schema Mappings

Belhajjame

Paton

et al. 2009

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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“…The choose-source operator described in the previous section is designed to deal with situations in which a n e n tire domain cluster can be mapped to a single in- 16 formation source through IS-links. But users will probably wish to write queries containing domain clusters that have r o l e s i n tended for mapping to di erent information sources.…”

Section: The Decompose Operatormentioning

confidence: 99%

Query reformulation for dynamic information integration

1996

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Abstract. The standard approach t o i n tegrating heterogeneous information sources is to build a global schema that relates all of the information in the di erent sources, and to pose queries directly against it. The problem is that schema integration is usually di cult, and as soon as any of the information sources change or a new source is added, the process may h a ve to be repeated.The SIMS system uses an alternative approach. A domain model of the application domain is created, establishing a xed vocabulary for describing data sets in the domain. Using this language, each a vailable information source is described. Queries to SIMS against the collection of available information sources are posed using terms from the domain model, and reformulation operators are employed to dynamically select an appropriate set of information sources and to determine how t o i n tegrate the available information to satisfy a query. This approach results in a system that is more exible than existing ones, more easily scalable, and able to respond dynamically to newly available or unexpectedly missing information sources. This paper describes the query reformulation process in SIMS and the operators used in it. We p r o vide precise de nitions of the reformulation operators and explain the rationale behind choosing the speci c ones SIMS uses. We h a ve demonstrated the feasibility and e ectiveness of this approach b y applying SIMS in the domains of transportation planning and medical trauma care.

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Managing heterogeneous information systems through discovery and retrieval of generic concepts

Srinivasan

Ngu

Gedeon

2000

J. Am. Soc. Inf. Sci.

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Autonomy of operations combined with decentralized management of data gives rise to a number of heterogeneous databases or information systems within an enterprise. These systems are often incompatible in structure as well as content and, hence, difficult to integrate. Depsite heterogeneity, the unity of overall purpose within a common application domain, nevertheless, provides a degree of semantic similarity that manifests itself in the form of similar data structures and common usage patterns of existing information systems. This article introduces a conceptual integration approach that exploits the similarity in metalevel information in existing systems and performs metadata mining on database objects to discover a set of concepts that serve as a domain abstraction and provide a conceptual layer above existing legacy systems. This conceptual layer is further utilized by an information reengineering framework that customizes and packages information to reflect the unique needs of different user groups within the application domain. The architecture of the information reengineering framework is based on an object‐oriented model that represents the discovered concepts as customized application objects for each distinct user group.

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Classifying schematic and data heterogeneity in multidatabase systems

Cited by 293 publications

References 7 publications

Defining and Using Schematic Correspondences for Automatically Generating Schema Mappings

Defining and Using Schematic Correspondences for Automatically Generating Schema Mappings

Query reformulation for dynamic information integration

Managing heterogeneous information systems through discovery and retrieval of generic concepts

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