scholarly journals AutoMed: A BAV Data Integration System for Heterogeneous Data Sources

2004 ◽  
pp. 82-97 ◽  
Author(s):  
Michael Boyd ◽  
Sasivimol Kittivoravitkul ◽  
Charalambos Lazanitis ◽  
Peter McBrien ◽  
Nikos Rizopoulos
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Integration System ◽  
Heterogeneous Data Sources ◽  
Data Integration System

Modern Manufacturing Enterprises Heterogeneous Data Integration System Based on Web Services

2012 ◽  
Vol 529 ◽  
pp. 356-360
Author(s):  
Xiao Xiao Liang ◽  
Shi Wen Li ◽  
Xu Zhan ◽  
Chong Gang Wei
Keyword(s):  
Web Services ◽  
Data Integration ◽  
Web Service ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Integration System ◽  
Heterogeneous Data Integration ◽  
Manufacturing Enterprises ◽  
Data Integration System ◽  
Modern Manufacturing

This webinar introduces an approach to data access across heterogeneous data sources and Web service integration based on XML and XQuery. The webinar covers: using XML to create logical views of a variety of physical data sources, aggregating XML documents with relational data, consuming Web services in XQuery, and exposing XQuery as data services while writing, testing and deploying real XML and XQuery-based solutions. The paper conducts web service and analyzes Modern Manufacturing Enterprises heterogeneous data source and proposes a heterogeneous data integration system based Web Services. The system provides a possible approach to share and interactive enterprise data.

scholarly journals Integração, Relacionamento e Representação de Dados em Cidades Inteligentes: Uma Revisão de Literatura

2018 ◽  
Author(s):  
Larysse Silva ◽  
José Alex Lima ◽  
Nélio Cacho ◽  
Eiji Adachi ◽  
Frederico Lopes ◽  
...  
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Data Integration ◽  
Smart Cities ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Application Development ◽  
Continuous Integration ◽  
Heterogeneous Data Sources ◽  
Computational Systems

A notable characteristic of smart cities is the increase in the amount of available data generated by several devices and computational systems, thus augmenting the challenges related to the development of software that involves the integration of larges volumes of data. In this context, this paper presents a literature review aimed to identify the main strategies used in the development of solutions for data integration, relationship, and representation in smart cities. This study systematically selected and analyzed eleven studies published from 2015 to 2017. The achieved results reveal gaps regarding solutions for the continuous integration of heterogeneous data sources towards supporting application development and decision-making.

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.

Data Warehouse Oriented Data Integration System Design and Implementation

2013 ◽  
Vol 321-324 ◽  
pp. 2532-2538
Author(s):  
Xiao Guo Wang ◽  
Jian Shen ◽  
Chuan Sun
Keyword(s):  
Data Integration ◽  
Data Warehouse ◽  
Heterogeneous Data ◽  
Information Process ◽  
Efficient Tool ◽  
Integration System ◽  
Related Information ◽  
Source Data ◽  
Data Integration System ◽  
Database Technology

Considering the difficulty of information collection and integration due to the rapid growth of information, we need an efficient tool to do these jobs. A proposal is be put forward to build a data integration system to collect the source data and preprocess the heterogeneous data and then convert/extract data to the data warehouse. Through experiment and analysis, this paper designed an information process flow and implemented the data integration system, based on B/S framework with the database technology, to deal with the college related information.

Research and Application on Oilfield Product Heterogeneous Data Integration Based on Ontology

2014 ◽  
Vol 530-531 ◽  
pp. 809-812
Author(s):  
Gang Huang ◽  
Xiu Ying Wu ◽  
Man Yuan ◽  
Rui Fang Li
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Distributed Data ◽  
Semantic Heterogeneity ◽  
Gas Industry ◽  
Heterogeneous Data Integration ◽  
Semantic Level ◽  
Heterogeneous Data Sources ◽  
Integrated Operations

The Oil & Gas industry is moving forward with Integrated Operations (IO). There are different ways to achieve data integration, and ontology-based approaches have drawn much attention. This paper introduces an ontology-based distributed data integration framework (ODDIF). 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. The proposed method reduces developing difficulty, improves developing efficiency, and enhances the maintainability and expandability of the system.

Research on the Expert System for Sweet Corn Standard Production Based on Heterologous Data Integration Technology

2013 ◽  
Vol 655-657 ◽  
pp. 1730-1733
Author(s):  
Lin Peng ◽  
Qiang Zheng ◽  
Zhao Rong Liu
Keyword(s):  
Expert System ◽  
Data Integration ◽  
Data Management ◽  
Sweet Corn ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Integration Technology ◽  
Shared Data ◽  
Heterogeneous Data Sources ◽  
Standard Production

To better share agricultural information in existed agricultural informatization condition, and to meet agro-departments new needs about local self-governed and global shared data management during standardized production of the sweet corn, this paper provides a method of integrated sharing of heterogeneous data sources to apply to standardized product of the sweet corn. This method solves the data integration and sharing problems during standardized production of the sweet corn. In this paper, the expert system for sweet corn standard production which is ability to combine heterogeneous data is constructed. This system is proved to be reliable, perform well and it is easy to operate.

scholarly journals An approach for semantic integration of heterogeneous data sources

2020 ◽  
Vol 6 ◽  
pp. e254
Author(s):  
Giuseppe Fusco ◽  
Lerina Aversano
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Semantic Integration ◽  
Data Sources ◽  
Complex Data ◽  
Semantic Heterogeneity ◽  
Heterogeneous Information ◽  
Heterogeneous Data Sources ◽  
Autonomous Data Sources ◽  
Unified View

Integrating data from multiple heterogeneous data sources entails dealing with data distributed among heterogeneous information sources, which can be structured, semi-structured or unstructured, and providing the user with a unified view of these data. Thus, in general, gathering information is challenging, and one of the main reasons is that data sources are designed to support specific applications. Very often their structure is unknown to the large part of users. Moreover, the stored data is often redundant, mixed with information only needed to support enterprise processes, and incomplete with respect to the business domain. Collecting, integrating, reconciling and efficiently extracting information from heterogeneous and autonomous data sources is regarded as a major challenge. In this paper, we present an approach for the semantic integration of heterogeneous data sources, DIF (Data Integration Framework), and a software prototype to support all aspects of a complex data integration process. The proposed approach is an ontology-based generalization of both Global-as-View and Local-as-View approaches. In particular, to overcome problems due to semantic heterogeneity and to support interoperability with external systems, ontologies are used as a conceptual schema to represent both data sources to be integrated and the global view.

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