A metadata modeling method for smart water management data analysis and sharing
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.
MetadataData lineageNeural networksSmart water management
NETL
NSTL
万方数据
