一种面向智慧水务数据分析与共享的元数据建模方法
A metadata modeling method for smart water management data analysis and sharing
薛浩 1袁丹 2李国富 3李美玲 2马静4
作者信息
- 1. 南京航空航天大学经济与管理学院,南京 211100;上海威派格智慧水务股份有限公司,上海 201800
- 2. 上海威派格智慧水务股份有限公司,上海 201800
- 3. 杭州市排水有限公司,杭州 310000
- 4. 南京航空航天大学经济与管理学院,南京 211100
- 折叠
摘要
随着智慧水务的逐步发展与成熟,建立统一的数据标准和规范对于提升数据质量、拓宽数据应用场景变得愈发重要,系统化的元数据建模成为智慧水务数据分析、共享与应用的关键.通过行业专家调研总结和水务大数据实施案例分析等多种方法,深入分析了原水获取、水厂处理、管网输配、营业计费等各个环节的数据构成要素,结合数据互操作性的需求,综合进行归纳与演绎,设计了一种面向智慧水务数据分析与共享的元数据框架.此外,还提出了一种融合BERT和TextCNN的混合卷积神经网络串行策略,用于增强元数据应用的共享能力.研究成果为智慧水务业务系统的拓展和数据深度应用提供了基础支撑.
Abstract
With the gradual development and maturity of smart water management,establis-hing unified data standards and specifications becomes increasingly crucial for enhancing data quali-ty and expanding data application scenarios.Systematic metadata modeling has become the key to data analysis,sharing,and application in smart water management.This paper,through various methods such as industry expert research,summary,and analysis of smart water management big data implementation cases,thoroughly analyzes the data elements in various stages such as raw wa-ter acquisition,water treatment plants,pipeline distribution,and business billing.Combining the requirements of data interoperability,the paper comprehensively summarizes and deduces,and de-signs a metadata framework tailored for smart water management data analysis and sharing.Addi-tionally,the paper proposes a hybrid convolutional neural network serial strategy that integrates BERT and TextCNN to enhance the shared capability of metadata applications.The research find-ings provide a foundational support for the expansion of smart water management business systems and the in-depth application of data.
关键词
元数据/数据血缘/神经网络/智慧水务Key words
Metadata/Data lineage/Neural networks/Smart water management引用本文复制引用
出版年
2024
NETL
NSTL
万方数据