A Data Model for Heterogeneous Data Integration Architecture

2014 ◽  
pp. 547-556 ◽  
Author(s):  
Michał Chromiak ◽  
Krzysztof Stencel
Keyword(s):  
Data Integration ◽  
Data Model ◽  
Heterogeneous Data ◽  
Heterogeneous Data Integration ◽  
Integration Architecture

scholarly journals Heterogeneous Data Integration Architecture-Challenging Integration Issues

2015 ◽  
Vol 15 (1) ◽  
pp. 7 ◽  
Author(s):  
Michal Chromiak ◽  
Marcin Grabowiecki
Keyword(s):  
Data Integration ◽  
Data Processing ◽  
System Integration ◽  
Current Trend ◽  
Heterogeneous Data ◽  
Heterogeneous Data Integration ◽  
Design Concepts ◽  
Integration Architecture ◽  
Efficient Data ◽  
Processing Engine

As of today, most of the data processing systems have to deal with a large amount of data originated from numerous sources. Data sources almost always differ regarding its purpose of existence. Thus model, data processing engine and technology differ intensely. Due to current trend for systems fusion there is a growing demand for data to be present in a common way regardless of its legacy. Many systems have been devised as a response to such integration needs. However, the present data integration systems mostly are dedicated solutions that bring constraints and issues when considered in general. In this paper we will focus on the present solutions for data integration, their flaws originating from their architecture or design concepts and present an abstract and general approach that could be introduced as an response to existing issues. The system integration is considered out of scope for this paper, we will focus particularly on efficient data integration.

VGEs-Oriented Multi-sourced Heterogeneous Data Integration

2010 ◽  
Vol 11 (3) ◽  
pp. 292-298
Author(s):  
Hongjun SU ◽  
Yehua SHENG ◽  
Yongning WEN ◽  
Min CHEN
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Heterogeneous Data Integration

Hierarchical Multi-Agent System for Heterogeneous Data Integration

2011 ◽  
pp. 165-186 ◽  
Author(s):  
Aleksander Byrski ◽  
Marek Kisiel-Dorohinicki ◽  
Jacek Dajda ◽  
Grzegorz Dobrowolski ◽  
Edward Nawarecki
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Multi Agent System ◽  
Agent System ◽  
Heterogeneous Data Integration ◽  
Multi Agent

Design and Implementation of Oilfield Heterogeneous Data Integration Model Based on Ontology

2014 ◽  
Vol 912-914 ◽  
pp. 1201-1204
Author(s):  
Gang Huang ◽  
Xiu Ying Wu ◽  
Man Yuan
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Semantic Heterogeneity ◽  
Integration Model ◽  
Integration Framework ◽  
Heterogeneous Data Integration ◽  
Semantic Level ◽  
Heterogeneous Data Sources ◽  
Semantic Difference

This paper provides an ontology-based distributed heterogeneous data integration framework (ODHDIF). The framework resolves the problem of semantic interoperability between heterogeneous data sources in semantic level. By metadatas specifying the distributed, heterogeneous data and by describing semantic information of data source , having "ontology" as a common semantic model, semantic match is established through ontology mapping between heterogeneous data sources and semantic difference institutions are shielded, so that semantic heterogeneity problem of the heterogeneous data sources can be effectively solved. It provides an effective technology measure for the interior information of enterprises to be shared in time accurately.

University Heterogeneous Data Source Integration Middleware Design Based on XML

2014 ◽  
Vol 543-547 ◽  
pp. 2937-2940
Author(s):  
Xiao Xiao Liang ◽  
Shun Min Wang ◽  
Chong Gang Wei ◽  
Chuang Shen
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Heterogeneous Data Source ◽  
Heterogeneous Data Integration ◽  
Data Source Integration ◽  
Data Source ◽  
The University

According to the distribution, autonomy and heterogeneity of the university database, we designed the structure, main arithmetic, query distribution device, result processor and wrapper of the university heterogeneous data integration middle ware by using Java, XML and middle ware. We emphasized on introducing the designation of query distribution device, result processor and wrapper.

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