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Data Integration

Ismael Navas‐Delgado, José F. Aldana‐Montes

Open publisher page 1 citations

Abstract

The growth of the Internet has simplified data access, which has involved an increment in the creation of new data sources. Despite this increment, in most cases, these large data repositories are accessed manually. This problem is aggravated by the heterogeneous nature and extreme volatility of the information on the Web. This heterogeneity includes three types: intentional (differences in the contents), semantic (differences in the interpretation), and schematic (data types, labeling, structures, etc.). Thus, the increase of the available information and the complexity of dealing with this amount of information have involved a considerable amount of research into the subject of heterogeneous data integration. The database community, one of the most important groups dealing with data heterogeneity and dispersion, has provided a wide range of solutions to this problem. However, this issue has also been addressed and solutions have been offered by the information retrieval and knowledge representation communities, making this area a connection point between the three communities.

About this research paper

What this paper is about

The growth of the Internet has simplified data access, which has involved an increment in the creation of new data sources. Despite this increment, in most cases, these large data repositories are accessed manually. This problem is aggravated by the heterogeneous nature and extreme volatility of the information on the Web. This heterogeneity includes three types: intentional (differences in the contents), semantic (differences in the interpretation), and schematic (data types, labeling, structures, etc.). Thus, the increase of the available information and the complexity of dealing with this amount of information have involved a considerable amount of research into the subject of heterogeneous data integration. The database community, one of the most important groups dealing with data heterogeneity and dispersion, has provided a wide range of solutions to this problem. However, this issue has also been addressed and solutions have been offered by the information retrieval and knowledge representation communities, making this area a connection point between the three communities.

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Available abstract

The growth of the Internet has simplified data access, which has involved an increment in the creation of new data sources. Despite this increment, in most cases, these large data repositories are accessed manually. This problem is aggravated by the heterogeneous nature and extreme volatility of the information on the Web. This heterogeneity includes three types: intentional (differences in the contents), semantic (differences in the interpretation), and schematic (data types, labeling, structures, etc.). Thus, the increase of the available information and the complexity of dealing with this amount of information have involved a considerable amount of research into the subject of heterogeneous data integration. The database community, one of the most important groups dealing with data heterogeneity and dispersion, has provided a wide range of solutions to this problem. However, this issue has also been addressed and solutions have been offered by the information retrieval and knowledge representation communities, making this area a connection point between the three communities.

Key concepts: Schematic, Computer science, Information integration, Data science, Semantic heterogeneity, Information retrieval, External Data Representation, Representation (politics)

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