Research on 3D Visualization and Data Management Integration Modeling of Digital Mine: A Case Study of Eastern Gejiu Sn-Cu Deposit in Yunnan Province, China

2014 ◽  
Vol 1073-1076 ◽  
pp. 2036-2041
Author(s):  
Ping Ping Yu ◽  
Jian Ping Chen ◽  
Miao Yu ◽  
Zhao Wu ◽  
Dong Yue Chen
Keyword(s):  
Big Data ◽  
Data Management ◽  
Information Integration ◽  
Yunnan Province ◽  
Production Management ◽  
3D Visualization ◽  
Management Platform ◽  
Digital Mine ◽  
Database Technology

In the era of big data, new information technologies introduced into the study of mining exploration to realize the wisdom prospecting has important significance. Based on 3S technology, 3D modeling and visualization technology, database technology and virtual reality technology, this paper studied the 3D integrated digital mine construction of big data era and presented a new concept of 3D visualization and data management integration modeling of digital mine. A case study of eastern Gejiu Sn-Cu deposit in Yunnan province of China achieved the integrated modeling of ground and underground, and also the multi-information integration and analysis of geology, geography, 2D and 3D. An integrated management platform was built in the application to integrate a variety of mine data organically, which provided support for mine production management, the deep prospecting practice and the comprehensive study and application of geological big data of mine.

scholarly journals Computer Data Storage and Management Platform Based on Big Data

2021 ◽  
Vol 2066 (1) ◽  
pp. 012022
Author(s):  
Cheng Luo
Keyword(s):  
Big Data ◽  
Data Management ◽  
Performance Improvement ◽  
Data Storage ◽  
Nonvolatile Memory ◽  
Linear Structure ◽  
Ring Structure ◽  
Computer Data ◽  
Management Platform ◽  
A Performance

Abstract Due to the continuous development of information technology, data has increasingly become the core of the daily operation of enterprises and institutions, the main basis for decision-making development. At the same time, due to the development of network, the storage and management of computer data has attracted more and more attention. Aiming at the common problems of computer data storage and management in practical work, this paper analyzes the object and content of data management, investigates the situation of computer data storage and management in China in recent two years, and interviews and tests the data of programming in this design platform. At the same time, in view of the related problems, the research results are applied to practice. On the basis of big data, the storage and management platform is designed. The research and design adopts a special B+ tree node linear structure of CIRC tree, and the linear node structure is changed into a ring structure, which greatly reduces the number of data persistence instructions and the performance overhead. The results show that compared with the most advanced B+ tree design for nonvolatile memory, crab tree has 3.1 times and 2.5 times performance improvement in reading and writing, respectively. Compared with the previous NV tree designed for nonvolatile memory, it has a performance improvement of 1.5 times, and a performance improvement of 8.4 times compared with the latest fast-fair. In the later stage, the expansion of the platform functions is conducive to the analysis and construction of data related storage and management functions, and further improve the ability of data management.

Extending Relational Data Model to Resolve the Conflicts in Schema Integration of Multiple Databases in Virtual Enterprise

1999 ◽  
Author(s):  
Z. M. Ma ◽  
W. J. Zhang ◽  
Q. Li
Keyword(s):  
Relational Database ◽  
Information Integration ◽  
Data Model ◽  
Production Management ◽  
Virtual Enterprise ◽  
Relational Data ◽  
Schema Integration ◽  
Essential Requirement ◽  
Relational Data Model

Abstract Virtual enterprise is typically one kind of information-based enterprise. The features of information system in virtual enterprise can be generalized as heterogeneous and distributed. Its organization and production management put an essential requirement on information integration. In this paper, we shall discuss the forms of conflict in schema integration of multiple databases in virtual enterprise, and give an approach to resolve the conflicts. In order to implement this approach in relational database, an extended relational data model is proposed and the notion of marked partial value is introduced. Based on this extended data model, some relational operations for data management are defined. A case study is discussed about query processing on relational database with partial values.

Big Data Management for Secure Information Integration

2017 ◽  
pp. 331-338
Author(s):  
Bhavani Thuraisingham ◽  
Mohammad Mehedy Masud ◽  
Pallabi Parveen ◽  
Latifur Khan
Keyword(s):  
Big Data ◽  
Data Management ◽  
Information Integration ◽  
Secure Information

BIG DATA PROCESSING: BIG CHALLENGES AND OPPORTUNITIES

2012 ◽  
Vol 13 (03n04) ◽  
pp. 1250009 ◽  
Author(s):  
CHANGQING JI ◽  
YU LI ◽  
WENMING QIU ◽  
YINGWEI JIN ◽  
YUJIE XU ◽  
...  
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Data Management ◽  
Data Storage ◽  
Large Scale ◽  
Distributed Applications ◽  
Big Data Processing ◽  
Cloud Data ◽  
Management Platform ◽  
Challenges And Opportunities

With the rapid growth of emerging applications like social network, semantic web, sensor networks and LBS (Location Based Service) applications, a variety of data to be processed continues to witness a quick increase. Effective management and processing of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing techniques from system and application aspects. First, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including definition of big data, big data management platform, big data service models, distributed file system, data storage, data virtualization platform and distributed applications. Following the MapReduce parallel processing framework, we introduce some MapReduce optimization strategies reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments.

scholarly journals A Methodological Workflow for Deriving the Association of Tourist Destinations Based on Online Travel Reviews: A Case Study of Yunnan Province, China

2021 ◽  
Vol 13 (9) ◽  
pp. 4720
Author(s):  
Tao Liu ◽  
Ying Zhang ◽  
Huan Zhang ◽  
Xiping Yang
Keyword(s):  
Big Data ◽  
Travel Behavior ◽  
Yunnan Province ◽  
Movement Patterns ◽  
User Generated Content ◽  
Great Opportunity ◽  
Tourist Destinations ◽  
Online Travel Reviews ◽  
Online Travel

Insights into the association rules of destinations can help to understand the possibility of tourists visiting a destination after having traveled from another. These insights are crucial for tourism industries to exploit strategies and travel products and offer improved services. Recently, tourism-related, user-generated content (UGC) big data have provided a great opportunity to investigate the travel behavior of tourists on an unparalleled scale. However, existing analyses of the association of destinations or attractions mainly depend on geo-tagged UGC, and only a few have utilized unstructured textual UGC (e.g., online travel reviews) to understand tourist movement patterns. In this study, we derive the association of destinations from online textual travel reviews. A workflow, which includes collecting data from travel service websites, extracting destination sequences from travel reviews, and identifying the frequent association of destinations, is developed to achieve the goal. A case study of Yunnan Province, China is implemented to verify the proposed workflow. The results show that the popular destinations and association of destinations could be identified in Yunnan, demonstrating that unstructured textual online travel reviews can be used to investigate the frequent movement patterns of tourists. Tourism managers can use the findings to optimize travel products and promote destination management.

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