期刊文献+

面向领域科学数据的虚拟数据空间共享模型 被引量:6

Virtual Data Space Sharing Model Towards Domain-specific Science Data
在线阅读 下载PDF
导出
摘要 以实现领域科学数据共享为目的,提出一种基于虚拟数据空间的共享模型.通过探讨模型中的主体、数据、服务与空间四要素,研究基于逻辑实体和逻辑实体集的领域科学数据聚合.针对领域内的各类应用主题以及个体的需求,将分散的领域科学数据聚集成与服务相关的虚拟数据空间,利用主体对服务的共享来实现数据的共享.最后,以石油领域油气井科研数据管理平台为例,阐述油气井科研数据共享的实现过程.实际应用表明,虚拟数据空间共享模型对于领域科学数据共享是高效可行的,并为数据密集型应用、领域内的服务开发与部署提供了良好的支持. To realize domain-specific science data sharing, a kind of data sharing model based on virtual data space is proposed in this paper. Discussing principals, data, service and space elements in this model,the research focused on domain-specific science data re- sources aggregation based on the logical entity and logical entity set. Towards various application theme and individual demand,the scattered domain-specific science data gathered to data space related service, by means of the sharing service to realize data sharing. Finally, Oil and gas well research data sharing platform as an example, the realization of virtual data space model towards oil and gas well research data sharing is described. The practice indicates that the virtual data space model to realize science data sharing is effi- cient and feasible, and provide good support for data-intensive application and service deployment.
出处 《小型微型计算机系统》 CSCD 北大核心 2014年第3期514-519,共6页 Journal of Chinese Computer Systems
基金 十二五国家科技支撑计划课题项目(2011BAK08B04)资助 材料领域知识工程北京市重点实验室2012年度阶梯计划项目(Z121101002812005)资助
关键词 领域科学数据 虚拟数据空间 逻辑实体 数据共享 domain-specific science data virtual data space logical entity data sharing
  • 相关文献

参考文献2

二级参考文献108

  • 1金澈清,钱卫宁,周傲英.流数据分析与管理综述[J].软件学报,2004,15(8):1172-1181. 被引量:163
  • 2谷峪,于戈,张天成.RFID复杂事件处理技术[J].计算机科学与探索,2007,1(3):255-267. 被引量:54
  • 3Deshpande A, viprin C, Madden S, Hellerstein J M, Hong W. Model-driven data acquisition in sensor networks// Proceedings of the 30th International Conference on Very Large Data Bases. Toronto, 2004:588-599
  • 4Madhavan J, Cohen S, Xin D, Halevy A, Jeffery S, Ko D, Yu C. Web-scale data integration: You can afford to pay as you go//Proceedings of the 33rd Biennial Conference on Innovative Data Systems Research. Asilomar, 2007:342-350
  • 5Liu Ling. From data privacy to location privacy: Models and algorithms (tutorial)//Proceedings of the 33rd International Conference on Very Large Data bases. Vienna, 2007: 1429- 1430
  • 6Samarati P, Sweeney L. Generalizing data to provide anonymity when disclosing information (abstract)//Proeeedings of the 17th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. Seattle, 1998:188
  • 7Cavallo R, Pittarelli M. The theory of probabilistic databases//Proceedings of the 13th International Conference on Very Large Data Bases. Brighton, 1987:71-81
  • 8Barbara D, Garcia-Molina H, Porter D. The management of probabilistic data. IEEE Transactions on Knowledge and Data Engineering, 1992, 4(5): 487-502
  • 9Fuhr N, Rolleke T. A probabilistic relational algebra for the integration of information retrieval and database systems. ACM Transactions on Information Systems, 1997, 15(1): 32-66
  • 10Zimanyi E. Query evaluation in probabilistic databases. Theoretical Computer Science, 1997, 171(1-2): 179-219

共引文献192

同被引文献103

引证文献6

二级引证文献37

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部