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Volume 34 Issue 5
Oct 2023
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Journal of Earth Science  > 2023  >  34(5): 1374-1389.
Qinjun Qiu, Bin Wang, Kai Ma, Hairong Lü, Liufeng Tao, Zhong Xie. A Practical Approach to Constructing a Geological Knowledge Graph: A Case Study of Mineral Exploration Data. Journal of Earth Science, 2023, 34(5): 1374-1389. doi: 10.1007/s12583-023-1809-3
Citation: Qinjun Qiu, Bin Wang, Kai Ma, Hairong Lü, Liufeng Tao, Zhong Xie. A Practical Approach to Constructing a Geological Knowledge Graph: A Case Study of Mineral Exploration Data. Journal of Earth Science, 2023, 34(5): 1374-1389. doi: 10.1007/s12583-023-1809-3
shu

A Practical Approach to Constructing a Geological Knowledge Graph: A Case Study of Mineral Exploration Data

doi: 10.1007/s12583-023-1809-3
  • 1.

    Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains, Zhengzhou 450046, China

  • 2.

    Key Laboratory of Spatiotemporal Perception and Intelligent Processing, Ministry of Natural Resources, Zhengzhou 450046, China

  • 3.

    Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences, Wuhan 430074, China

  • 4.

    Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering, China Three Gorges University, Yichang 443002, China

  • 5.

    College of Computer and Information Technology, China Three Gorges University, Yichang 443002, China

  • 6.

    Department of Automation, Tsinghua University, Beijing 100084, China

More Information
  • Corresponding author: Kai Ma, makai@ctgu.edu.cn
  • Received Date: 05 Jun 2022
  • Accepted Date: 09 Dec 2022
    • Available Online: 14 Oct 2023
  • Issue Publish Date: 30 Oct 2023
    Abstract

  • Open data initiatives have promoted governmental agencies and scientific organizations to publish data online for reuse. Research of geoscience focuses on processing georeferenced quantitative data (e.g., rock parameters, geochemical tests, geophysical surveys and satellite imagery) for discovering new knowledge. Geological knowledge is the cognitive result of human knowledge of the spatial distribution, evolution and interaction patterns of geological objects or processes. Knowledge graphs (KGs) can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently. In this paper, we propose a novel framework that can extract the geological knowledge graph (GKG) from public reports relating to a modelling study. Based on the analysis of basic questions answered by geology, we summarize and abstract geological knowledge elements and then explore a geological knowledge representation model with three levels of "geological concepts-geological entities-geological relations" to describe semantic units of geological knowledge and their logic relations. Finally, based on the characteristics of mineral resource reports, the geological knowledge representation model oriented to "object relationships" and the hierarchical geological knowledge representation model oriented to "process relationships" are proposed with reference to the commonly used geological knowledge graph representation. The research in this paper can provide some implications for the formalization and structured representation of geological knowledge graphs.

     

    • Conflict of Interest
    The authors declare that they have no conflict of interest.
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