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面向高校多源异构数据环境的元数据集成方法 被引量:8

A Metadata Integration Method Oriented Multi-source Heterogeneous Data Environment of Colleges
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摘要 高校信息化建设已由各类应用开发为主的数字化校园阶段发展到以系统整合为主的智慧校园阶段,当前工作难点在于多源异构数据集成的存储成本、传输成本均较高,且对网络带宽有很高的要求.考虑使用本体和元数据所蕴含的丰富语义信息可以极大降低数据集成成本,提出了一种面向高校多源异构数据环境的元数据集成方法.该方法首先构建局部本体,在局部本体基础上生成高校领域本体,同时抽取局部元数据;然后在高校领域本体的指导下对局部元数据进行集成,得到全局元数据;最后,在高校实际环境中进行了实例分析.分析结果表明所提方法切实可行,用元数据集成替代数据集成能够避免大量数据的存储和传输,有效降低数据集成的成本. The construction of information technology in colleges has developed from a digital campus stage with various application developments to a smart campus stage with system integration.The current work difficulty lies in the high storage cost and high network bandwidth of multi-source heterogeneous data integration.Considering the rich semantic information contained in ontology and metadata can greatly reduce the cost of data integration,a metadata integration method oriented multi-source heterogeneous data environment of colleges is proposed.The method first constructs a local ontology,generates a college domain ontology based on the local ontology,and extracts local metadata at the same time;Integrate local metadata under the guidance of college domain ontology to get global metadata.Finally,an instance analysis is carried out in the actual environment of colleges.The analysis results show that the proposed method is feasible,and metadata integration instead of data integration avoids the storage and transmission of large amounts of data,effectively reducing the cost of data integration.
作者 冯勇 张丽颖 顾兆旭 马技 FENG Yong;ZHANG Li-ying;GU Zhao-xu;MA Ji(College of Information,Liaoning University,Shenyang 110036,China;Computer Department of Liaoning Vocational College of Light Industry,Dalian 116100,China;Information Center,Liaoning University of Traditional Chinese Medicine,Shenyang 110847,China)
出处 《辽宁大学学报(自然科学版)》 CAS 2019年第2期135-141,共7页 Journal of Liaoning University:Natural Sciences Edition
基金 辽宁中医药大学2018年度教学改革研究项目(LNZYJG2018041) 2018年辽宁省普通高等教育本科教学改革研究项目立项优质教学资源建设与共享项目(互联网+视域下大学计算机基础课程在线教育模式研究)
关键词 数据集成 语义 本体 元数据 异构 data integration semantics ontology metadata heterogeneous
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