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Knowledge graph for multi-source data: optimizing the systematic layout and application of reference materials for
Bin Wang1, Yuena Jiang2, Jiangnan Wang2
1National Institute of Metrology, No. 18, Bei San Huan Dong Lu, Beijing, 100029, China. wangbin@nim.ac.cn.
Analytical and Bioanalytical Chemistry
|May 29, 2026
Summary
This study integrates fragmented data on edible agricultural products, creating a knowledge graph to improve nutrition and safety reference materials. This enhances resource utilization and supports food safety development.
Area of Science:
- Agricultural Science
- Food Science
- Information Science
Background:
- China's edible agricultural products sector faces challenges like fragmented data and poor resource integration, particularly for nutrition and safety reference materials.
- Existing resources for reference materials are often siloed, hindering systematic research and application in food safety.
- There is an underexplored potential in leveraging systematic resources for enhancing food safety standards.
Purpose of the Study:
- To address the lack of structure and weak resource linkage in China's edible agricultural products sector.
- To improve the utilization of systematic resources for nutrition and safety reference materials.
- To build a comprehensive knowledge base by interlinking diverse data sources.
Main Methods:
- In-depth analysis of edible agricultural product classification and nutrition/safety testing indicators.
- Application of visualized knowledge graph technology to map and reference heterogeneous data.
- Systematic collection, processing, and integration of massive datasets into a knowledge base.
Main Results:
- A comprehensive knowledge graph system was constructed by interlinking reference materials, testing standards, literature, and institutions.
- The knowledge graph system was successfully deployed online, bridging isolated data resources.
- The platform facilitates multidimensional knowledge exploration and promotes a systematic framework for reference material research.
Conclusions:
- The study successfully transformed fragmented data into integrated, high-quality resources for reference materials.
- The developed knowledge graph system significantly enhances the ability to leverage aggregated resources in food safety.
- This approach provides substantial support for the development and application of reference materials, improving food safety standards.
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