GB/T 45032-2024Smart city - Knowledge trustworthiness assessment for urban governance scenarios (English PDF)

Foreword

This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part

1.Structure and drafting rules for standardization documents" Drafting. Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents. This document was proposed and coordinated by the National Technical Committee for Information Technology Standardization (SAC/TC28). This document was drafted by: Shandong Provincial Computing Center (National Supercomputing Jinan Center), China Electronics Technology Standardization Institute, Yantai Huang Bohai New Area Management Committee, Jiangsu Solid Internet of Things Co., Ltd., Shandong New Generation Standardization Research Institute Co., Ltd., Peking University, China United Network Communications Co., Ltd. Shandong Branch, Ziguang Yida Technology (Shandong) Co., Ltd., JD City (Beijing) Digital Technology Co., Ltd. Company, Inspur Smart Technology Co., Ltd., Renmin University of China, China Mobile Xiong'an Information and Communication Technology Co., Ltd., Huawei Technologies Co., Ltd., China Electronics Great Wall Internet System Application Co., Ltd., Southwest Jiaotong University, Digital China Information System Co., Ltd., Beijing Big Data Center, Xinhua Big Data Data Technology Co., Ltd., Yantai Zhidian Intelligent Technology Co., Ltd., Qilu University of Technology (Shandong Academy of Sciences), Hainan Aviator Technology Co., Ltd. Co., Ltd., Sichuan Yili Digital City Technology Co., Ltd., Suzhou Sugaoxin Digital Technology Co., Ltd., Guangdong Cheweishi Information Technology Co., Ltd. Co., Ltd., Mingpai Technology Group Co., Ltd., Chengdu Guoheng Space Technology Engineering Co., Ltd., and Shushang (Zhejiang) Technology Co., Ltd. The main drafters of this document are. Gao Yongchao, Wang Yan, Wang Dejian, Qian Heng, Wang Yaoyao, Zhao Junfeng, An Xiaomi, Zheng Qingguo, Zhang Hongwei, Min Jinghua, Zhang Junbo, Feng Xiaomeng, Wang Jinzhu, Ma Yufei, Chen Xiaozhong, Du Shengdong, Zhang Ding, Qi Dong, Yang Xiaolin, Lu Xiaojian, Huang Ning, Wang Qiuyue, Zhou Ru, Chen Yun, Chen Hongfeng, Mo Ran, Yang Bin, Leng Haitao, Li Liqin, Ke Songyu, Guo Wenyi, Li Xiaoye, Tang Wei, Jiang Qing, Liu Yang, Wang Yasha, Zhang Junning, Xu Chuan, Liu Juntao, Zhang Ruoding, Wu Xin, Yang Yuanbing.

Smart cities rely on massive amounts of data and integrate advanced information technology to continuously improve urban management efficiency, optimize public services, and enhance The knowledge in the smart city field refers to the objects, events, concepts or rules in the city, the relationships between them and Abstract information about attributes that is organized and applied for scenario-oriented system use. Knowledge is the core of smart cities. It enables city managers to make more scientific, reasonable and efficient urban decisions and promote the sustainable development of smart cities. With the continuous deepening of smart city construction, the urban governance field relies more and more on knowledge. In the information environment, how to improve the credibility of the knowledge used has become a key issue that needs to be urgently addressed in the field of urban governance. Knowledge trustworthiness refers to the ability of knowledge to meet the expectations of stakeholders in a verifiable manner, which covers the reliability of the source of knowledge, In smart cities, this knowledge is widely used in various fields of urban governance, such as intelligent dispatching, government affairs, etc. Customer service, environmental monitoring, traffic management, etc., their reliability is directly related to the efficiency and effectiveness of urban governance. In order to standardize the knowledge trustworthiness assessment work in the field of urban governance in smart cities and improve the level of intelligent urban governance, this document proposes The framework defines the four core areas of knowledge trustworthiness assessment in the field of urban governance. The core units are knowledge trust demand analysis, knowledge trust feature identification, knowledge trust feature measurement, knowledge trust level evaluation and feedback. This provides a systematic guide for evaluating the trustworthiness of knowledge in the field of urban governance in smart cities. The builders and operators of smart cities should scientifically and systematically evaluate the trustworthiness of knowledge in a complex and ever-changing information environment, thereby selecting Meet user needs, reliable knowledge, and provide strong support for urban governance. At the same time, this framework also provides a reference for knowledge management, It provides reference and reference for the formulation of relevant standards such as knowledge services. Smart city knowledge for urban governance is trustworthy Evaluation Framework

1 Scope

China's national framework for assessing the trustworthiness of knowledge in smart city urban governance applications. The problem it addresses is real and current: a city governance platform aggregates data and derived knowledge from dozens of departments and vendors - traffic models, population estimates, risk scores, rules learned from data - and then makes decisions with it. The knowledge is of very unequal quality. Some is a statutory register, some is an inference from sensors of unknown calibration, some is a model whose training data no longer resembles the city. Nothing in the platform distinguishes them, and a decision made on the weakest input looks exactly like one made on the strongest. The framework sets out how to analyse trustworthiness requirements, identify and measure the features that bear on them, evaluate the result and feed it back, so that unreliable knowledge can be screened out before it is acted on.

This paper provides a knowledge trustworthiness assessment framework for urban governance application scenarios in smart cities, including knowledge trustworthiness requirements analysis, analysis, feature identification, feature measurement, trustworthiness evaluation and feedback. This document is applicable to the evaluation of the trustworthiness of knowledge in urban governance application scenarios in smart cities, in order to screen out knowledge that meets user needs. of reliable knowledge.

2 Normative references

This document has no normative references.

3 Terms and definitions

The following terms and definitions apply to this document.

3.1 Knowledge Knowledge, judgment or skill acquired through study, practice or exploration. Note 1 to entry. Knowledge can be explicit or tacit; organizational or personal. Note 2 to entry. Knowledge may include factual knowledge, principle knowledge, skill knowledge and interpersonal knowledge. Note

3.Knowledge is information that has been "edited" and can bring real value to the organization after being processed in a meaningful context and analyzed. The knowledge behind the successful technology, successful products and effective strategies. The collection of organizational knowledge (accumulated experience, employees, management skills, operating methods, Note

4.Data is a record of objective facts, information is processed data, which is a meaningful interpretation of data, and knowledge is the in-depth understanding of information. Understand and apply. [Source: GB/T 23703.2-2010, 2.1, modified]

3.2 entity Concrete or abstract things in the field under consideration. [Source: ISO 8000-2.2022, 3.3.3]

3.3 Model An abstract representation of a system or other thing or process. [Source: GB/T 36332-2018, 3.6]

3.4 Knowledge model A structured specification of real facts in a particular domain. [Source: ISO 18308.2011, 3.38]