2009Unpublished venueRequires access

Integrating schemas of heterogeneous relational databases through schema matching

Yaser Karasneh, Hamidah Ibrahim, Mohamed Othman, Razali Yaakob

Open publisher page 6 citations

Abstract

Database integration aims at providing a uniform and consistent view called global schema, over a set of autonomous and heterogeneous data sources, so that data residing in different sources can be accessed as if it was in a single schema. The integration of databases' schemas can be performed in four main phases, namely: preintegration, comparing of the schemas, conforming of the schemas, and merging and restructuring. The second and third phases can be combined and normally is known as schema matching. Schema matching, the focus of this paper, is a fundamental operation in the manipulation of schema in formatting match, which takes two schemas that correspond semantically to each other. Manually specifying schema matches is a tedious, time consuming, error-prone, and therefore expensive process, which is a growing problem given the rapidly increasing number of data sources to integrate. As systems become able to handle more complex databases and applications, their schemas become large, further increasing the number of matches to be performed. Thus, automating this process, which attempts to achieve faster and less labor-intensive, has been one of the main tasks in data integration. However, it is not possible to determine fully automatically the different correspondences between schemas, primarily because of the differing and often not explicated or documented semantics of the schemas. Several solutions in solving the issues of schema matching have been proposed. Nevertheless, these solutions are still limited, as they do not explore most of the available information related to schemas and thus affect the result of integration. This paper presents an approach for integrating heterogeneous relational databases' schemas through schema matching that utilizes most of the information related to schemas, which indirectly explores the implicit semantics of the schemas, that further improves the results of the integration. This paper also shows that the produced integrated schemas (global schemas) maintained the properties of the initial input schemas and also the characteristics of the relational model.

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What this paper is about

Database integration aims at providing a uniform and consistent view called global schema, over a set of autonomous and heterogeneous data sources, so that data residing in different sources can be accessed as if it was in a single schema. The integration of databases' schemas can be performed in four main phases, namely: preintegration, comparing of the schemas, conforming of the schemas, and merging and restructuring. The second and third phases can be combined and normally is known as schema matching. Schema matching, the focus of this paper, is a fundamental operation in the manipulation of schema in formatting match, which takes two schemas that correspond semantically to each other. Manually specifying schema matches is a tedious, time consuming, error-prone, and therefore expensive process, which is a growing problem given the rapidly increasing number of data sources to integrate. As systems become able to handle more complex databases and applications, their schemas become large, further increasing the number of matches to be performed. Thus, automating this process, which attempts to achieve faster and less labor-intensive, has been one of the main tasks in data integration. However, it is not possible to determine fully automatically the different correspondences between schemas, primarily because of the differing and often not explicated or documented semantics of the schemas. Several solutions in solving the issues of schema matching have been proposed. Nevertheless, these solutions are still limited, as they do not explore most of the available information related to schemas and thus affect the result of integration. This paper presents an approach for integrating heterogeneous relational databases' schemas through schema matching that utilizes most of the information related to schemas, which indirectly explores the implicit semantics of the schemas, that further improves the results of the integration. This paper also shows that the produced integrated schemas (global schemas) maintained the properties of the initial input schemas and also the characteristics of the relational model.

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Available abstract

Database integration aims at providing a uniform and consistent view called global schema, over a set of autonomous and heterogeneous data sources, so that data residing in different sources can be accessed as if it was in a single schema. The integration of databases' schemas can be performed in four main phases, namely: preintegration, comparing of the schemas, conforming of the schemas, and merging and restructuring. The second and third phases can be combined and normally is known as schema matching. Schema matching, the focus of this paper, is a fundamental operation in the manipulation of schema in formatting match, which takes two schemas that correspond semantically to each other. Manually specifying schema matches is a tedious, time consuming, error-prone, and therefore expensive process, which is a growing problem given the rapidly increasing number of data sources to integrate. As systems become able to handle more complex databases and applications, their schemas become large, further increasing the number of matches to be performed. Thus, automating this process, which attempts to achieve faster and less labor-intensive, has been one of the main tasks in data integration. However, it is not possible to determine fully automatically the different correspondences between schemas, primarily because of the differing and often not explicated or documented semantics of the schemas. Several solutions in solving the issues of schema matching have been proposed. Nevertheless, these solutions are still limited, as they do not explore most of the available information related to schemas and thus affect the result of integration. This paper presents an approach for integrating heterogeneous relational databases' schemas through schema matching that utilizes most of the information related to schemas, which indirectly explores the implicit semantics of the schemas, that further improves the results of the integration. This paper also shows that the produced integrated schemas (global schemas) maintained the properties of the initial input schemas and also the characteristics of the relational model.

Key concepts: Schema matching, Computer science, Schema migration, Information schema, Schema (genetic algorithms), Database schema, Data integration, Conceptual schema

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