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Copyright of Journal of Academic Library & Information Science is the property of Anhui University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Hubei Open Vocational College is the property of Journal of Hubei Open Vocational College Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Medical Education Technology is the property of China Medical Education Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cyber Security & Data Governance is the property of Editorial Office of Information Technology & Network Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cyber Security & Data Governance is the property of Editorial Office of Information Technology & Network Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Geospatial Information Verification Mid-End Platform for Natural Resource Administration is designed in response to issues such as repeated development, low scalability, and inconsistent verification rules in existing approval and supervision application systems. We first discussed the architecture of the middle platform and micro-services and also examined the business requirements. Secondly, we presented the architecture of the spatial information verification platform. Finally, the application method in the construction land approval business is introduced. Practical applications proved that the spatial information verification platform is highly scalable and maintainable, with reusable business components and data services for a variety of government affairs application systems. [ABSTRACT FROM AUTHOR]

The data middle platform is the data base of intelligent coal mine construction and the foundation of coal mine big data application. This paper proposes the idea of intelligent coal mine data middle platform construction, including data aggregation, data development, data storage, data asset management and data service. This study designs the intelligent coal mine data middle platform architecture, analyzes the data standard specification, big data basic support, data aggregation, data development, data resource pool, data asset management, data service, operation and maintenance guarantee and other function modules of the data middle platform. This paper discusses the solutions of key technologies such as large concurrency and low latency data processing, data classification and storage, data governance, and the construction of big data-based coal mine disaster-risk model in the process of building an intelligent coal mine data middle platform. The application shows that the intelligent coal mine data middle platform realizes data aggregation, data development, as well as the data classification and storage of various perception data, basic data and management data, data asset management, data modeling, model training and data services, etc. The platform makes the multi-source heterogeneous data of coal mines change from data resources to data assets, provides applications such as scheduling decision, disaster risk analysis, equipment health diagnosis and preventive maintenance based on big data, and solves the problems of serious information silos, difficult data integration and low level of intelligent analysis in coal mines.

Some problems existed in data governance in the process of coal mine automation, digitalization and information construction are analyzed, which include: top-level design is weak, supportive capability of data platform is failure, data fusion and analysis capability is insufficient, ubiquitous perception network and perception equipments are lack, etc. For the above problems, framework and development path of data governance in intelligent coal mine are proposed. The overall framework of data governance in intelligene coal mine includes data source layer, data middle platform service layer, data application layer and infrastructure layer. The development path of data governance in intelligene coal mine includes improving overall holographic information data collection of coal mine, building data middle platform suitable for coal mine, developing data application integrating intelligent decision-making, and consolidating infrastructure guarantee of coal mine data governance.

The overall framework of State Grid ubiquitous power IoT and the layered architecture of data middle platform were analyzed.The positioning and application mode of SG-CIM in data middle platform,and the support of model for data analysis application were studied.The physical model design of data middle platform was put forward,on the premise of adopting the baseline version control,parallel expansion tables and joint views was created for personalized model expansion design.As to the integrated implementation of model data for data middle platform,combining database selection and adopt bulk data loading was proposed,so as to improve efficiency of data integration.As for the upgrading and updating of data middle platform model,creating a middle table to minimize the impact on the data analysis application was recommended,and a good support was achieved for the data analysis application based on data middle platform.

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To address the data ‘islandization’ issue in the statistical field and to take advantage of the opportunity of the Statistical Cloud construction, the National Bureau of Statistics of China (NBS) started adopting the concept of a “data middle platform” for data resource planning. With it, NBS aims to build a comprehensive data capability platform that includes data collection and exchange; data sharing and integration; data organizing and processing; data modeling and analyses; data management and governance; and data service and application. The statistical data middle platform provides the basic capability for data application support. It also enables data to form a closed loop between the data middle platform and the business system, and eventually realizes the ‘servitization’ of statistical data that meets internal and societal requirements. As a new innovative development, the statistical data middle platform will not only solve the long-standing data island problem of NBS but will also provide a basic guarantee for greater use of the data potential, and thus will help official statistics to transform from statistical analysis to predictive analysis, from single-domain to cross-domain, from passive analysis to active analysis, and from non-real-time to real-time analysis. The paper was prepared under the kind mentorship of Ronald Jansen, Assistant Director and Chief of Data Innovation at the UN Statistics Division in New York. [ABSTRACT FROM AUTHOR]

The overall framework of State Grid ubiquitous power IoT and the layered architecture of data middle platform were analyzed. The positioning and application mode of SG-CIM in data middle platform, and the support of model for data analysis application were studied. The physical model design of data middle platform was put forward, on the premise of adopting the baseline version control, parallel expansion tables and joint views was created for personalized model expansion design. As to the integrated implementation of model data for data middle platform, combining database selection and adopt bulk data loading was proposed, so as to improve efficiency of data integration. As for the upgrading and updating of data middle platform model, creating a middle table to minimize the impact on the data analysis application was recommended, and a good support was achieved for the data analysis application based on data middle platform. [ABSTRACT FROM AUTHOR]