GB/T 43208.2-2025Information technology service - Intelligent operation and maintenance - Part 2: Data governance (English PDF)

Foreword

This document complies with the provisions of GB/T 1.1-2020 "Standardization Work Guidelines Part

1.Structure and Drafting Rules of Standardization Documents". Drafting. This document is Part 2 of GB/T 43208 "Intelligent Operation and Maintenance of Information Technology Services". GB/T 43208 has already published the following... part.

1.General Requirements;

2.Data Governance. Please note that some content in this document may involve patents. The issuing organization of this document assumes no responsibility for identifying patents. This document was proposed and is under the jurisdiction of the National Information Technology Standardization Technical Committee (SAC/TC28). This document was drafted by: China Southern Power Grid Digital Grid Group Co., Ltd., Taiping Insurance Technology Co., Ltd., China Merchants Securities Co., Ltd., and Guangfa Securities Co., Ltd. Guangdong Provincial Rural Credit Cooperative Union, Guangfa Bank Co., Ltd., Ping An Bank Co., Ltd., China Bond Fintech Information Technology Co., Ltd. China Everbright Bank Co., Ltd., Agricultural Bank of China Limited, China Electronics Technology Standardization Institute, China Construction Bank Joint-stock limited companies, Guotai Junan Securities Co., Ltd., Shanghai Pudong Development Bank Co., Ltd., Bank of Beijing Co., Ltd. People's Insurance Company of China Limited, Air China Limited, Changjiang Securities Co., Ltd., and Shanghai Bank Co., Ltd. Limited Liability Company, Industrial Securities Co., Ltd., Guizhou Power Grid Co., Ltd. Information Center, CITIC Securities Co., Ltd., Shenwan Hongyuan Securities Co., Ltd. Hongyuan Securities Co., Ltd., GF Securities Co., Ltd., China Electric Power Research Institute Co., Ltd., State Grid Hebei Electric Power Co., Ltd. Information and Communication Branch, China Southern Power Grid Co., Ltd. Ultra-High Voltage Transmission Company, Beijing Zhongguancun Laboratory, China Sports Lottery Technology Development Co., Ltd. Limited Liability Company, Kunlun Digital Technology Co., Ltd., Shanghai Pudong Development Bank Co., Ltd. Credit Card Center, Beijing Information Science and Technology University, China Railway Design Group Co., Ltd., China Unicom Digital Technology Co., Ltd., CCB Financial Technology Co., Ltd., China United Network Communications Limited Liability Company, PICC Information Technology Co., Ltd., COSCO Shipping Technology Co., Ltd., Shanghai Stock Exchange Data Service Co., Ltd., Yunzhi Hui (Beijing) Technology Co., Ltd., Shanghai Newtek Software Co., Ltd., Inspur Cloud Information Technology Co., Ltd., Yunnan Nantian Electronic Information Industry Co., Ltd. Industry Co., Ltd., Shanghai Dingmao Information Technology Co., Ltd., Shanghai Firethorn Fruit Digital Technology Co., Ltd., Shanghai Hanwei Information Technology Co., Ltd. company. The main drafters of this document are. Chen Qingming, Wei Jiaohua, Cai Jian, Deng Shuguang, Chen Jun, Tang Haiyong, Chen Jie, Peng Xiao, Guo Xinwei, Shi Qinghong, and Pan Jin. Li Lifeng, Fu Shouqing, Shi Hongyu, Lu Weikai, Zou Wenjing, Chen Xiaojian, Zhan Jie, Chen Peng, Shen Dabing, Du Yingjun, Zhang Ningjun, Li Jiesong, Tan Like Xia Limin, Ye Mingji, Xu Dawei, Geng Hao, Ding Ye, Wu Yong, Wei Yaohui, Fu Qian, Geng Peng, Liu Chengjiang, Zhang Ming, Li Wen, Huang Huo, Lin Yunzhang, Guan Jun Hou Tongxu, Zhang Yan, Gao Nan, Wei Xiaoming, Zhou Rui, Zhao Wenlong, Lin Maojun, Cui Liqun, Chi Ye, Li Shizhe, Xue Ke, Ma Jing, Long Yujiang, Gan Rundong Xu Zhibin, Li Baoqiang, Yu Sisong, Bao Hubao, Peng Huasheng, Xu Yinghui, Zhao Jing, Wu Junying, Yang Liping, Li Zhuohui, Xu Chao, Jiang Jing, Meng Xianlong Tang Jinrui, Wang Yeping, Yang Yuli, Li Xiaoluan, Tie Jincheng, Li Hu, Jin Chunhua, Xu Fangqiu, Han Yu, Liu Yuenan, He Yuxiang, Zhang Zaifeng, Chen Zhigang Kong Xiangjian, Wang Shuang, Guo Lei, Wang Junxiang, Du Jianxin, Weng Zhenbang, Lu Xinghai, Wang Shuhang, Kou Zuliang, Wang Hao, Zhang Mufei, Liu Xiaoyu, Zeng Dongruo Gong Baonan, Xu Haitao, Shen Hui, Liu He, Shen Xiaoxiao, Liang Guiying, Chen Hongfeng, Pan Gang, Huang Xing.

With the rapid development of technologies such as artificial intelligence, big data, and cloud computing, operation and maintenance services are shifting from being driven by systems and processes to being driven by data and computing. The era of law-driven intelligent operation and maintenance is evolving. Intelligent operation and maintenance, as an important application of artificial intelligence in the field of operation and maintenance, represents a brand-new approach in the field. GB/T 43208, based on industry development and organizational practices, establishes a capability framework for intelligent operation and maintenance, while also addressing the issues from the perspectives of data, algorithms, and technology. Requirements were set forth from the perspective of various capability elements. Among these, data is the cornerstone of intelligent operation and maintenance, algorithms are the key to unlocking the value of data, and technology is the means to achieve [the goal]. Intelligent operation and maintenance methods. The relationship between the various parts is shown in Figure 1. Figure

1.Relationship between the parts of GB/T 43208 GB/T 43208 is proposed to consist of four parts.

1.General Requirements. The aim is to provide an intelligent operations framework for intelligent operations organizations, guiding them from organizational governance, intelligence... We will carry out intelligent operation and maintenance construction from three aspects. operation and maintenance scenario implementation, capability domain, etc., to continuously improve the level of intelligent operation and maintenance and achieve operation and maintenance goals.

2.Data Governance. The aim is to provide intelligent operations and maintenance organizations with an operational data governance framework, guiding them in managing their capability domains. Data elements are governed to provide high-quality operation and maintenance data for intelligent operation and maintenance construction, effectively supporting intelligent operation and maintenance scenarios. accomplish.

3.Operations Algorithm Governance. The aim is to provide intelligent operations organizations with an operations algorithm governance framework, guiding organizations in their capability domains. By governing the algorithmic elements within the framework, we can provide secure, reliable, and effective operation and maintenance algorithms for intelligent operation and maintenance construction, and mine operation and maintenance data. Value, enabling the realization of operation and maintenance scenarios.

4.Operations Technology Governance. The aim is to provide intelligent operations organizations with an operations technology governance framework to guide organizations in their capacity domains. The governance of technical elements within the framework provides principles, methods, and requirements for the application of technology in intelligent operation and maintenance (O&M) construction, supporting intelligent O&M sites. The realization of the scene. This document inherits and draws upon the theoretical methods of traditional business data governance, and, considering the characteristics of operations and maintenance data, clarifies the governance rights for operations and maintenance data. A governance framework will be established to form an operations and maintenance data governance system, providing high-quality and comprehensive operations and maintenance data to better support intelligent operations and maintenance scenarios. This approach effectively addresses core operational data issues such as inconsistent data quality and a lack of targeted standards. Intelligent Operation and Maintenance of Information Technology Services Part

1 Scope

GB/T 43208.2-2025 is the Chinese national standard covering the data an AIOps system runs on - the logs, metrics, traces and events, their collection and retention, their quality and labelling, and the governance without which the anomaly detection learns from noise. Part 2 of the series, first edition. It was issued on 2 December 2025 and has been in force since 1 July 2026, as a first edition. The document is under the responsibility of the Standardization Administration of China. This page is published from the official record of the 2025 edition; the clause text of a standard this recent is not yet in circulation, and the figures, limits and tables it contains are those of the document itself, delivered in full with the English translation.

This document establishes a data governance framework for intelligent operations and maintenance (O&M), specifying top-level design, O&M data management, O&M data supply, and O&M data... According to the requirements of the governance process. This document is intended to guide organizations in conducting operations and maintenance data governance, to help organizations assess their own operations and maintenance data governance conditions and capabilities, and to enable customers to evaluate suppliers. Operations and maintenance data governance capabilities; third-party assessment of the provider's operations and maintenance data governance capabilities.

2 Normative references

The contents of the following documents, through normative references within the text, constitute essential provisions of this document. Dated citations are not included. For references to documents, only the version corresponding to that date applies to this document; for undated references, the latest version (including all amendments) applies. This document.

GB/T 43208.1-2023 Intelligent Operation and Maintenance of Information Technology Services - Part

3 Terms and Definitions

The terms and definitions defined in GB/T 43208.1-2023, as well as the following terms and definitions, apply to this document.

3.1 The operation and maintenance activities involve configurations, monitoring, processes, management, and logs related to the operation and maintenance objects or operations, or are directly or indirectly derived from them. The data.

3.2 In intelligent operation and maintenance scenarios, the operation and maintenance data resources involved include related control activities, performance management, and risk management during application processes. gather.

3.3 By defining data requirements through an operations and maintenance data model, we can guide the distributed control and integration of operations and maintenance data assets and deploy an integrated operation and maintenance data environment. Environment and operation and maintenance metadata management.

3.4 An abstraction of operational data is used to describe the characteristics, structure, and relationships between operational data.

3.5 Data that may be valuable to the organization during its operations and maintenance activities, including documents, materials, and charts. General term.