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Paleontology Knowledge Graph for Data-Driven Discovery

  • Yiying Deng,
  • Sicun Song,
  • Junxuan Fan,
  • Mao Luo,
  • Le Yao,
  • Shaochun Dong,
  • Yukun Shi,
  • Linna Zhang,
  • Yue Wang,
  • Haipeng Xu,
  • Huiqing Xu,
  • Yingying Zhao,
  • Zhaohui Pan,
  • Zhangshuai Hou,
  • Xiaoming Li,
  • Boheng Shen,
  • Xinran Chen,
  • Shuhan Zhang,
  • Xuejin Wu,
  • Lida Xing,
  • Qingqing Liang,
  • Enze Wang

摘要

A knowledge graph (KG) is a knowledge base that integrates and represents data based on a graph-structured data model or topology. Geoscientists have made efforts to construct geoscience-related KGs to overcome semantic heterogeneity and facilitate knowledge representation, data integration, and text analysis. However, there is currently no comprehensive paleontology KG or data-driven discovery based on it. In this study, we constructed a two-layer model to represent the ordinal hierarchical structure of the paleontology KG following a top-down construction process. An ontology containing 19 365 concepts has been defined up to 2023. On this basis, we derived the synonymy list based on the paleontology KG and designed corresponding online functions in the OneStratigraphy database to showcase the use of the KG in paleontological research.