Measurement Data Management System Based on Graph Computing

DOI: https://doi.org/10.62517/jbdc.202501416

Author(s)

Beiling Qiu1, Lingdong Meng1, Qiongxin Liu1, Yang Shen2, Shengqiong Yuan2,3,*

Affiliation(s)

1Hubei Institute of Metrology and Testing Technology, Wuhan, China 2School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China 3Hubei Key Laboratory of Digital Finance Innovation, Hubei University of Economics, Wuhan, China *Corresponding Author

Abstract

Metering refers to activities carried out for achieving uniform unit, accurate and reliable measurement values. This study intends to explore the key technologies of a measurement data storage system based on graph computing, so as to address the challenges faced by traditional structured data architectures when processing massive, multi-dimensional, and diverse-format measurement data. The core contents of the study include: analyzing the quantity traceability system and the requirements of different measurement activity scenarios, researching and establishing a graph storage architecture for measurement data, and designing a GAS graph storage programming model with balanced computing load. Based on the measurement and testing data, measurement primary and standard data of our institute, research and design work such as data dictionary modeling, database scripting, and graphical user interface (GUI) development are carried out, and a digital interaction method for measurement data graph storage is formed. In addition, this report extracts a general data storage method suitable for thermal radiation measurement data and data storage during experiments, according to the data and structures defined in the existing technical specifications of the thermal radiation field. It also establishes a knowledge graph based on experimental data in the thermal radiation field, which is applicable to thermal radiation institutions for knowledge management and query during experimental work.

Keywords

Measurement Data; Storage System; Knowledge Graph Construction; Graph Visualization

References

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