Research and Application of Business-Driven Classification System for Atmospheric Environmental Data Resources

Probe - Environmental Science and Technology

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Field Value
 
Title Research and Application of Business-Driven Classification System for Atmospheric Environmental Data Resources
 
Creator Huang, Jiaqi
 
Subject Atmospheric Environment; Big Data; Information Sharing
 
Description This article discusses the functional transformation of classification in knowledge management on the basis of summarizing the development of classification system, and analyzes the category characteristics and limitations of environmental industries under different classification systems. In this article, the idea and content of data classification and metadata service of the Federal Enterprise Architecture Framework (FEA Framework), which is a classification system with data sharing as the core under the background of big data transmission, are sorted out. The construction of comprehensive data collection and sharing platform for atmospheric environmental science is taken as an example to explore the business-driven scientific data sharing system. The result shows that with the transformation of knowledge carrier and dissemination mode, classification method has changed from knowledge structure, knowledge discovery to sharing. With the use principle of co-construction and sharing of network information, knowledge community and government information, the method has changed from traditional subject classification to business-oriented, which includes 11 categories to develop a metadata registry and full-text retrieval services to meet the characteristics of big data use.
 
Publisher Universe Scientific Publishing Pte. Ltd.
 
Contributor
 
Date 2020-06-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://probe.usp-pl.com/index.php/PES/article/view/1334
10.18686/pes.v2i2.1334
 
Source Probe - Environmental Science and Technology; Vol 2, No 2 (2020); 46-49
2661-3948
 
Language eng
 
Relation http://probe.usp-pl.com/index.php/PES/article/view/1334/1179
 
Rights Copyright (c) 2020 Jiaqi Huang
http://creativecommons.org/licenses/by-nc/4.0
 

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