Services of Earth System Science Data Sharing Based on Cloud Computing

  • 1. College of Computer and Information Engineering of Henan University, Kaifeng 475004, China;

    2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

Received date: 2013-07-01

  Revised date: 2013-11-01

  Online published: 2014-03-10


Geoscience is a science of data-intensive research, whose process is dependent on the data resources and information platform. Especially for earth system science, in order to understand how the earth runs as a whole and to reveal the driving force of global environmental change, it is urgent to implement data sharing. Early geoscience data sharing services are primarily of data concentration and archiving by the government behaviors, which has many prominent problems such as imbalanced load of data service, simplex pattern of integrated data, indistinctive effect of data services, etc. We aimed to set up a new geoscience research environment that every researcher is both the user and the contributor of geoscience resources. With the present of Web2.0 and the emergence of cloud computing technology, data sharing mode has undertaken great changes. This paper presented the concept model, function structure and technology system of earth system science data sharing based on cloud computing, and built a prototype system of "geoscience data sharing services based on cloud service". This system embodies a transition of service mode by Infrastructure as a Service (IaaS), Data Resources as a Service (DaaS) and Data Software as a Service (SaaS). It ensures data security and realizes the Data Access Load Balancing based on the master-slave data storage technology. In the cloud service system of data sharing environment for geosciences research, everyone is both data producer and user. It can solve the data sharing contradiction between "user and data" by providing data publishing, data needs publishing, data finding/sharing, data needs finding/feedback and other functions. Finally, through the study of earth system science based on cloud computing and the key technique of data sharing we have built a prototype system to validate the framework. The cloud service system can improve the sharing and utilization of resources, enhance the on-demand service mode and provide an extensive and compatible scientific data sharing environment.

Cite this article

MIAO Ru, ZHU Yunqiang, SONG Jia, FENG Min, PAN Peng . Services of Earth System Science Data Sharing Based on Cloud Computing[J]. Journal of Geo-information Science, 2014 , 16(2) : 264 -272 . DOI: 10.3724/SP.J.1047.2014.00264


[1] 孙九林,林海.地球系统研究与科学数据[M].北京:科学出版社,2009.

[2] 汪品先.我国的地球系统科学研究向何处去[J].地球科学进展,2003,18(6):837-851.

[3] 孙枢.对我国全球变化与地球系统科学研究的若干思考[J].地球科学进展,2005,20(1):6-10.

[4] 诸云强, 宋佳, 冯敏, 等. 地球系统科学数据共享软件研究与发展[J]. 中国科技资源导刊, 2012(6):11-16.

[5] Goodchild M F. Citizens as sensors: The world of volunteered geography[J]. GeoJournal, 2007,69(4):211-221.

[6] 李德仁,邵振峰.论新地理信息时代[J].中国科学 (F辑: 信息科学),2009,39(6):579-587.

[7] 刘刚,董树文,陈宣华,等.EarthScope——美国地球探测计划及最新进展[J].地质学报,2010(6):909-926.

[8] Nambiar U, Ludaescher B, Lin K, et al. The GEON portal: Accelerating knowledge discovery in the geosciences[C]. Arlington, VA, United States: Association for Computing Machinery, 2006.

[9] Meertens C, Wier S, Murray D, et al. The GEON IDV (Integrated Data Viewer) for data exploration and discovery in the geosciences[C]. AGU Fall Meeting Abstracts, 2006.

[10] Beard D. Using VRML to share large volumes of complex 3D geoscientific information via the Web[C]//Proceedings of the Eleventh International Conference on 3D Web Technology. ACM, 2006: 163-167.

[11] Beard D J, Hay R J, Nicoll M G, et al. 3D Web Mapping -3D Geoscience Information Online[C]. Proceedings of SSC 2005 Spatial Intelligence, Innovation and Praxis: The National Biennial Conference of the Spatial Sciences Institute, September, 2005, Melbourne: Spatial Sciences Institute.

[12] Chubak G, Morozov I. Integrated software framework for processing of geophysical data[J]. Computers & Geosciences, 2006(32):767-775.

[13] Bai Y Q, Di L P, Wei Y X. A taxonomy of geospatial services for global service discovery and interoperability[J]. Computer & Geosciences, 2009(35):783-790.

[14] 王卷乐,孙九林.世界数据中心(WDC)回顾,变革与展望[J].地球科学进展,2009,24(6):612-620.

[15] Zhu Y Q, Rajan Bajracharya. Towards a regional geographic data-sharing network in the Himalayas[C]. Sustainable Mountain Development No. 60, ICIMOD, Autumn,2011.

[16] 诸云强.地球系统科学数据共享平台建设与服务[J].中国科技投资,2011(12):27-29.

[17] 诸云强,冯敏,宋佳,等.基于SOA的地球系统科学数据共享平台架构设计与实现[J].地球信息科学学报,2009,11(1):1-9.

[18] 诸云强,孙九林,廖顺宝,等.地球系统科学数据共享研究与实践[J].地球信息科学学报,2010,12(1):1-8.

[19] 刘润达,诸云强,宋佳,等.一种简单跨域单点登录系统的实现[J].计算机应用,2007,27(2):288-291.

[20] 耿庆斋,朱星明.水利科学数据共享标准体系研究与构建[J].水利学报,2007,38(2):233-238.

[21] 刘真,刘峰,张宝鹏,等.云计算模型在铁路大规模数据处理中的应用[J].北京交通大学学报,2010,34(5):14-19.

[22] Goscinski A, Brock M. Toward dynamic and attribute based publication, discovery and selection for cloud computing[J]. Future Generation Computer Systems, 2010,26(7):947-970.

[23] Zhang G, Xie C, Shi L, et al. A tile-based scalable raster data management system based on HDFS[C]. IEEE 20th International Conference on Geoinformatics (GEOINFORMATICS), 2012.

[24] 罗慧敏,阎朝坤.一种基于任务竞争力的工作流调度算法[J].河南大学学报(自然科学版),2012,42(1):87-91.