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...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 conceptsgeological 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.展开更多
基金the IUGS Deep-time Digital Earth(DDE)Big Science Programfinancially supported by the National Key R&D Program of China(No.2022YFF0711601)+4 种基金the Natural Science Foundation of Hubei Province of China(No.2022CFB640)the Opening Fund of Hubei Key Laboratory of Intelligent Vision-Based Monitoring for Hydroelectric Engineering(No.2022SDSJ04)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(No.GLAB 2023ZR01)the Fundamental Research Funds for the Central UniversitiesFunded by Joint Fund of Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains,Henan Province and Key Laboratory of Spatiotemporal Perception and Intelligent processing,Ministry of Natural Resources(No.212205)。
文摘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 conceptsgeological 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.
