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Ontology-driven relational data mapping for constructing a knowledge graph of porphyry copper deposits

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Abstract

Geoscience knowledge graph has become a popular topic in recent years. A series of studies have been reported to introduce the construction and application of geoscience knowledge graphs from different views. The relational geoscience dataset with high knowledge density and data quality is an important digital heritage of geoscience. The relational dataset has not been taken seriously in the geoscience knowledge graph research. In this study, we proposed a quick method of building a geoscience knowledge graph using relational data mapping to triples. First, the use-case-driven method was applied to design the ontology of porphyry copper deposits. Second, the mapping rules were built based on the porphyry copper ontology. Third, the knowledge graph of the porphyry copper deposit was constructed based on relational data mapping and knowledge fusion. Based on the resulting knowledge graph, several exploratory cases were conducted to make knowledge reasoning and discovery. It is indicated that the solution proposed in this study is a fast batch-processing geoscience knowledge graph construction method. The experiences from this study can benefit the construction of knowledge graphs in other geoscience disciplines and promote knowledge discovery.

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Data availability

The dataset of porphyry copper deposits can be obtained from US Geological Survey (https://mrdata.usgs.gov/porcu/). The file of mapping rules is available on GitHub at https://github.com/wangcug/DataMapping.

Code availability

The mapping rules file is available on GitHub at https://github.com/wangcug/DataMapping.

Notes

  1. http://d2rq.org/d2rq-language#propertybridge.

  2. https://mrdata.usgs.gov/porcu/.

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Funding

This study was funded by the National Key R&D Program of China (2022YFF0801202, 2022YFF0801200), National Natural Science Foundation of China (41902305), Knowledge Innovation Program of Wuhan-Shuguang (2023010201020332).

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Authors and Affiliations

  1. State Key Laboratory of Geological Processes and Mineral Resources & School of Earth Resources, University of Geosciences, Wuhan, 430074, China

    Chengbin Wang, Liangquan Tan, Yuanjun Li, Mingguo Wang & Jianguo Chen

  2. Powerchina Zhongnan Engineering Corporation Limited, Changsha, 410021, China

    Liangquan Tan

  3. Mineral Resources Exploration Center of Henan Geological Bureau, Zhengzhou, 450012, China

    Yuanjun Li

  4. Yunnan Geological Big Data Center, Geological Survey and Mapping Institute of Yunnan Province, Kunming, 650218, China

    Mingguo Wang

  5. Department of Computer Science, University of Idaho, 875 Perimeter Drive, MS 1010, Moscow, ID, 83844-1010, USA

    Xiaogang Ma

Authors
  1. Chengbin Wang
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  2. Liangquan Tan
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  3. Yuanjun Li
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  4. Mingguo Wang
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  5. Xiaogang Ma
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Contributions

ChengbinWang: writing-original draft, conceptualization, data validation, writing-review and editing, project administration, funding acquisition. Liangquan Tan: building the mapping rules. Yuanjun Li: knowledge graph visualization and application. Mingguo Wang: writing-review and editing. Xiaogang Ma: writing-review and editing, data validation. Jianguo Chen: funding acquisition, data validation, writing-review, and editing.

Corresponding author

Correspondence to Chengbin Wang.

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The authors declare no competing interests.

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Communicated by H. Babaie.

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Wang, C., Tan, L., Li, Y. et al. Ontology-driven relational data mapping for constructing a knowledge graph of porphyry copper deposits. Earth Sci Inform (2024). https://doi.org/10.1007/s12145-024-01307-5

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