A materials terminology knowledge graph automatically constructed from text corpus

Yuwei Zhang; Fangyi Chen; Zeyi Liu; Yunzhuo Ju; Dongliang Cui; Jinyi Zhu; Xue Jiang; Xi Guo; Jie He; Lei Zhang; Xiaotong Zhang; Yanjing Su

doi:10.1038/s41597-024-03448-0

Scientific Data (Jun 2024)

A materials terminology knowledge graph automatically constructed from text corpus

Yuwei Zhang,
Fangyi Chen,
Zeyi Liu,
Yunzhuo Ju,
Dongliang Cui,
Jinyi Zhu,
Xue Jiang,
Xi Guo,
Jie He,
Lei Zhang,
Xiaotong Zhang,
Yanjing Su

Affiliations

Yuwei Zhang: School of Computer and Communication Engineering, University of Science and Technology Beijing
Fangyi Chen: School of Computer and Communication Engineering, University of Science and Technology Beijing
Zeyi Liu: School of Computer and Communication Engineering, University of Science and Technology Beijing
Yunzhuo Ju: School of Computer and Communication Engineering, University of Science and Technology Beijing
Dongliang Cui: School of Computer and Communication Engineering, University of Science and Technology Beijing
Jinyi Zhu: School of Computer and Communication Engineering, University of Science and Technology Beijing
Xue Jiang: Beijing Advanced Innovation Center for Materials Genome Engineering, Institute for Advanced Materials and Technology, University of Science and Technology Beijing
Xi Guo: School of Computer and Communication Engineering, University of Science and Technology Beijing
Jie He: School of Computer and Communication Engineering, University of Science and Technology Beijing
Lei Zhang: Beijing Advanced Innovation Center for Materials Genome Engineering, Institute for Advanced Materials and Technology, University of Science and Technology Beijing
Xiaotong Zhang: School of Computer and Communication Engineering, University of Science and Technology Beijing
Yanjing Su: Beijing Advanced Innovation Center for Materials Genome Engineering, Institute for Advanced Materials and Technology, University of Science and Technology Beijing

DOI: https://doi.org/10.1038/s41597-024-03448-0
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 11

Abstract

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Abstract A scalable, reusable, and broad-coverage unified material knowledge representation shows its importance and will bring great benefits to data sharing among materials communities. A knowledge graph (KG) for materials terminology, which is a formal collection of term entities and relationships, is conceptually important to achieve this goal. In this work, we propose a KG for materials terminology, named Materials Genome Engineering Database Knowledge Graph (MGED-KG), which is automatically constructed from text corpus via natural language processing. MGED-KG is the most comprehensive KG for materials terminology in both Chinese and English languages, consisting of 8,660 terms and their explanations. It encompasses 11 principal categories, such as Metals, Composites, Nanomaterials, each with two or three levels of subcategories, resulting in a total of 235 distinct category labels. For further application, a knowledge web system based on MGED-KG is developed and shows its great power in improving data sharing efficiency from the aspects of query expansion, term, and data recommendation.

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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