{"title":"用于构建斑岩型铜矿床知识图谱的本体驱动关系数据映射","authors":"Chengbin Wang, Liangquan Tan, Yuanjun Li, Mingguo Wang, Xiaogang Ma, Jianguo Chen","doi":"10.1007/s12145-024-01307-5","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":49318,"journal":{"name":"Earth Science Informatics","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ontology-driven relational data mapping for constructing a knowledge graph of porphyry copper deposits\",\"authors\":\"Chengbin Wang, Liangquan Tan, Yuanjun Li, Mingguo Wang, Xiaogang Ma, Jianguo Chen\",\"doi\":\"10.1007/s12145-024-01307-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":49318,\"journal\":{\"name\":\"Earth Science Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Earth Science Informatics\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s12145-024-01307-5\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth Science Informatics","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s12145-024-01307-5","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Ontology-driven relational data mapping for constructing a knowledge graph of porphyry copper deposits
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.
期刊介绍:
The Earth Science Informatics [ESIN] journal aims at rapid publication of high-quality, current, cutting-edge, and provocative scientific work in the area of Earth Science Informatics as it relates to Earth systems science and space science. This includes articles on the application of formal and computational methods, computational Earth science, spatial and temporal analyses, and all aspects of computer applications to the acquisition, storage, processing, interchange, and visualization of data and information about the materials, properties, processes, features, and phenomena that occur at all scales and locations in the Earth system’s five components (atmosphere, hydrosphere, geosphere, biosphere, cryosphere) and in space (see "About this journal" for more detail). The quarterly journal publishes research, methodology, and software articles, as well as editorials, comments, and book and software reviews. Review articles of relevant findings, topics, and methodologies are also considered.