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企业数据空间的数据组织方法研究 被引量:1

Research on Data Organization Method Based on Enterprise DataSpace
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摘要 企业数据空间的主体是整个企业,面向多个部门、专业或项目,数据规模巨大、种类复杂多样,还需要管理大量已有严格数据模式的数据库,数据组织管理困难。然而现有数据空间的数据组织方法,大多是基于个人数据空间的,无法满足企业数据空间复杂的数据管理需求。为了统一描述多源异构数据、多维多角度地灵活组织数据和将传统的“先模式后数据”和数据空间的“先数据后模式”方式协调起来进行管理,提出了企业数据空间的数据组织方法:通过构建分层组织模型实现对数据多维多角度地灵活组织;利用属性图模型对企业数据空间中的各种数据资源进行统一描述和管理。基于该方法可以更好地描述企业中的各种数据资源,为企业提供灵活高效的数据组织和管理方式,进而更好地支持企业数据空间的数据模式演化,提高企业的数据管理效率,满足企业的数据组织管理需求。 The main body of the enterprise data space is the entire enterprise,facing multiple departments,professions,or projects.The scale of the data is huge,and the types are complex and diverse.It also needs to manage a large number of databases with strict data models,which makes data organization and management difficult.However,the existing data organization methods of data space are mostly based on personal data space,which cannot meet the complex data management requirements of enterprise data space.In order to uniformly describe multi-source heterogeneous data,organize data flexibly in multiple dimensions and multiple angles,and coordinate the traditional“first model first data”and data space“first data first mode”methods for management,a data organization for enterprise data space is proposed.A multi-dimensional and multi-angle flexible organization of data is achieved by constructing a hierarchical organization model;a unified description and management of various data resources in the enterprise data space is made by using the attribute graph model.Based on this method,various data resources in the enterprise can be better described,and flexible and efficient data organization and management methods can be provided for enterprises,so as to better support the data model evolution of the enterprise data space,improve the data management efficiency of the enterprise,and meet the needs of enterprise data organization and management.
作者 文必龙 焦圣杰 郭娇 WEN Bi-long;JIAO Sheng-jie;GUO Jiao(School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318,China)
出处 《计算机技术与发展》 2020年第12期56-60,65,共6页 Computer Technology and Development
基金 国家自然科学基金面上项目(41574117) 国家重大专项(2016ZX05033-005-004) 大庆市指导性科技计划项目(zd-2019-22)。
关键词 企业数据空间 数据组织 数据资源目录 属性图 数据模型 enterprise dataspace data organization data resource catalog property graph data model
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  • 1杜小勇,李曼,王珊.本体学习研究综述[J].软件学报,2006,17(9):1837-1847. 被引量:241
  • 2LiuBing.Web数据挖掘[M].北京:清华大学出版社,2009.
  • 3寇玉波 李玉坤 孟小峰等.个人数据空间管理中的任务挖掘策略.计算机研究与发展,2009,46(2).
  • 4Liu Zhcngtao, Mao Yuguang.A data model for web dataspaces management[C]//IEEE International Symposium on Education and Computer Science.Wuhan, China: IEEE Computer Society, 2009.
  • 5Dong Xin, Halevy A Y.A platform for personal information management and integration[C]//Proceedings of the 2nd Conference on Innovative Data Systems Research, Asilomar, CA, 2005 : 119-130.
  • 6Karger D R, Bakshi K.Haystack: a customizable general-purpose information management tool for end users of semistructured data[C]//Proceedings of the 2nd Conference on Innovative Data Systems Research, Asilomar, CA, 2005: 13-26.
  • 7Levy A, Rajaraman A.Querying heterogeneous information sources using source descriptions[C]//Proceedings of 22nd International Conference on Very Large Data Bases.San Fransisco:Morgan Kaufmann, 1996:251-262.
  • 8Agrawal S, Chaudhuri S.Dbxplorer: a system for keyword-based search over relational databases[C]//Proceedings of the 18th International Conference on Data Engineering.San Jose, CA: IEEE Computer Society, 2002: 5-16.
  • 9Cohen S,Mamou J.Xsearch:a semantic search engine for XML[C]//Proceedings of 29th International Conference on Very Large Data Bases.Berlin, Germany: Morgan Kaufmann, 2003:45-56.
  • 10He H,Wang H.Blinks:ranked keyword searches on graphs[C]// Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data.Beijing, China: ACM Press, 2007: 305-316.

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