Wang Xuezhi, Zhao Jianghua, Zhou Yuanchun, Liao Jianhui
{"title":"The Geospatial Data Cloud: An Implementation of Applying Cloud Computing in Geosciences","authors":"Wang Xuezhi, Zhao Jianghua, Zhou Yuanchun, Liao Jianhui","doi":"10.2481/DSJ.14-042","DOIUrl":null,"url":null,"abstract":"The rapid growth in the volume of remote sensing data and its increasing computational requirements bring huge challenges for researchers as traditional systems cannot adequately satisfy the huge demand for service. Cloud computing has the advantage of high scalability and reliability, which can provide firm technical support. This paper proposes a highly scalable geospatial cloud platform named the Geospatial Data Cloud, which is constructed based on cloud computing. The architecture of the platform is first introduced, and then two subsystems, the cloud-based data management platform and the cloud-based data processing platform, are described. ––– This paper was presented at the First Scientific Data Conference on Scientific Research, Big Data, and Data Science, organized by CODATA-China and held in Beijing on 24-25 February, 2014.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Science Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2481/DSJ.14-042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 9
Abstract
The rapid growth in the volume of remote sensing data and its increasing computational requirements bring huge challenges for researchers as traditional systems cannot adequately satisfy the huge demand for service. Cloud computing has the advantage of high scalability and reliability, which can provide firm technical support. This paper proposes a highly scalable geospatial cloud platform named the Geospatial Data Cloud, which is constructed based on cloud computing. The architecture of the platform is first introduced, and then two subsystems, the cloud-based data management platform and the cloud-based data processing platform, are described. ––– This paper was presented at the First Scientific Data Conference on Scientific Research, Big Data, and Data Science, organized by CODATA-China and held in Beijing on 24-25 February, 2014.
期刊介绍：
The Data Science Journal is a peer-reviewed electronic journal publishing papers on the management of data and databases in Science and Technology. Details can be found in the prospectus. The scope of the journal includes descriptions of data systems, their publication on the internet, applications and legal issues. All of the Sciences are covered, including the Physical Sciences, Engineering, the Geosciences and the Biosciences, along with Agriculture and the Medical Science. The journal publishes papers about data and data systems; it does not publish data or data compilations. However it may publish papers about methods of data compilation or analysis.
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