Research on Heterogeneous Data Access and Integration Model Based on OGSA-DAI

Gao, Jiangjin; Xiao, Jing

doi:10.1109/iccis.2013.441

Cited by 2 publications

(2 citation statements)

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“…The discussed works present a process of integrating data sources seeking to address structural and semantic heterogeneity using layered frameworks or architectures, presenting a unified view for data queries. The works by Assaf et al (2012), Gao, Xiao (2013) and Saes (2019) present a semi-automatic integration process while the works by Pelekis, Theodoridis and Janssens (2014) and Madkour, Aref and Basalamah (2013) automatically and respectively present solutions for these through the use of ontologies, ETL of semantic data, semantic cubes and frameworks.…”

Section: Considerations On the Resolution Of Semantic Heterogeneity Through Data Analysismentioning

confidence: 99%

Review and comparison of works on heterogeneous data and semantic analysis in Big Data

et al. 2021

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In integration approaches, heterogeneity is one of the main challenging factors on the task of providing integration among different data sources, whose solution lies in the search for equality among them. This work describes the state of the art and theoretical foundation involved in the structural and semantic analysis of heterogeneous data and information. The work aims to review methods and techniques used in data integration in Big Data, considering data heterogeneity, reviewing techniques that use the concepts of Semantic Web, Cloud Computing, Data Analysis, Big Data, Data Warehouse and other technologies to solve the problem of data heterogeneity. The research was divided into three stages. In the first stage, articles were selected from digital libraries according to their titles and keywords. In the second stage, the papers went through a second filter based on their summary, and, besides that, duplicate articles were also removed. The works’ introduction and conclusion were analyzed in the third stage to select the articles belonging to this systematic review. Throughout the study, articles were analyzed, compared and categorized. At the end of each section, the interrelationships and possible areas for future work were shown.

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Section: Considerations On the Resolution Of Semantic Heterogeneity Through Data Analysismentioning

confidence: 99%

Review and comparison of works on heterogeneous data and semantic analysis in Big Data

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Additionally, there are a number of studies and research related to heterogeneous data integration based on, for instance, XML ( Fengguang, Xie, & Liqun, 2009 ) ( Su, Fan, & Li, 2010 ) ( Lin, 2009 ), Lucene and XQuery ( Tianyuan, Meina, & Xiaoqi, 2010 ), and OGSA-DAI ( Gao & Xiao, 2013 ). In the same way, heterogeneous data integration has applications to many areas, such as Livestock Products Traceability ( Chen & Liu, 2009 ), safety production ( Han, Tian, & Wu, 2009 ), management information systems ( Hailing & Yujie, 2012 ), medical information ( Shi, Liu, Xu, & Ji, 2010 ), and web environments ( Fan & Gui, 2007 ).…”

Section: Bibliographical Reviewmentioning

confidence: 99%