Big Data Management for Cloud-Enabled Geological Information Services

Author:

Zhu Yueqin12ORCID,Tan Yongjie12ORCID,Luo Xiong34ORCID,He Zhijie34ORCID

Affiliation:

1. Development and Research Center, China Geological Survey, Beijing 100037, China

2. Key Laboratory of Geological Information Technology, Ministry of Land and Resources, Beijing 100037, China

3. School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing 100083, China

4. Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing 100083, China

Abstract

Cloud computing as a powerful technology of performing massive-scale and complex computing plays an important role in implementing geological information services. In the era of big data, data are being collected at an unprecedented scale. Therefore, to ensure successful data processing and analysis in cloud-enabled geological information services (CEGIS), we must address the challenging and time-demanding task of big data processing. This review starts by elaborating the system architecture and the requirements for big data management. This is followed by the analysis of the application requirements and technical challenges of big data management for CEGIS in China. This review also presents the application development opportunities and technical trends of big data management in CEGIS, including collection and preprocessing, storage and management, analysis and mining, parallel computing based cloud platform, and technology applications.

Funder

Key Laboratory of Geological Information Technology of Ministry of Land and Resources

Publisher

Hindawi Limited

Subject

Computer Science Applications,Software

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