A practical approach to building a calcareous nannofossil knowledge graph

IF 2.4 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Geoscience Data Journal Pub Date : 2024-10-09 DOI:10.1002/gdj3.279
Hongyi Zhao, Bin Hu, Chao Ma, Shijun Jiang, Yi Zhang, Xin Li, Lirong Chen, Can Cai, Longgang Ye, Shengjian Zhou, Chengshan Wang
{"title":"A practical approach to building a calcareous nannofossil knowledge graph","authors":"Hongyi Zhao,&nbsp;Bin Hu,&nbsp;Chao Ma,&nbsp;Shijun Jiang,&nbsp;Yi Zhang,&nbsp;Xin Li,&nbsp;Lirong Chen,&nbsp;Can Cai,&nbsp;Longgang Ye,&nbsp;Shengjian Zhou,&nbsp;Chengshan Wang","doi":"10.1002/gdj3.279","DOIUrl":null,"url":null,"abstract":"<p>Following sustained development, numerous palaeontology databases and datasets of various types have been created. However, the lack of a unified standard language to describe knowledge and unclear sharing mechanisms between different databases and datasets has limited the large-scale integration and application of paleontological data. The knowledge graph, as a key technology for semantic translation and data fusion, offers a possible solution to these challenges. Given the potential of knowledge graphs to overcome these obstacles, this paper presents a practical approach to express paleontological knowledge in a knowledge graph via the resource description framework language. By delving into the structured data associated with calcareous nannofossil biozones (the UC zone, CC zone and NC zone), we propose an ontology to describe the semantic units and logical relationships of paleontological biozones and species and then integrate relevant species records from unstructured research reports to construct a knowledge graph for calcareous nannofossils, that integrates multisource paleobiological data and knowledge reconstruction. Our focus lies in detailing the technical aspects of constructing a paleontological knowledge graph. The results demonstrate that knowledge graphs can integrate semistructured and unstructured paleontological data from various sources. This work aims to assist palaeontologists in building and utilizing knowledge graphs, serving as an initial effort for future paleontological knowledge reasoning.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.279","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscience Data Journal","FirstCategoryId":"89","ListUrlMain":"https://rmets.onlinelibrary.wiley.com/doi/10.1002/gdj3.279","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Following sustained development, numerous palaeontology databases and datasets of various types have been created. However, the lack of a unified standard language to describe knowledge and unclear sharing mechanisms between different databases and datasets has limited the large-scale integration and application of paleontological data. The knowledge graph, as a key technology for semantic translation and data fusion, offers a possible solution to these challenges. Given the potential of knowledge graphs to overcome these obstacles, this paper presents a practical approach to express paleontological knowledge in a knowledge graph via the resource description framework language. By delving into the structured data associated with calcareous nannofossil biozones (the UC zone, CC zone and NC zone), we propose an ontology to describe the semantic units and logical relationships of paleontological biozones and species and then integrate relevant species records from unstructured research reports to construct a knowledge graph for calcareous nannofossils, that integrates multisource paleobiological data and knowledge reconstruction. Our focus lies in detailing the technical aspects of constructing a paleontological knowledge graph. The results demonstrate that knowledge graphs can integrate semistructured and unstructured paleontological data from various sources. This work aims to assist palaeontologists in building and utilizing knowledge graphs, serving as an initial effort for future paleontological knowledge reasoning.

Abstract Image

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
构建钙质化石知识图谱的实用方法
经过持续发展,已经创建了许多不同类型的古生物学数据库和数据集。然而,缺乏统一的标准语言来描述知识,不同数据库和数据集之间的共享机制不明确,限制了古生物数据的大规模集成和应用。知识图谱作为语义翻译和数据融合的关键技术,为这些挑战提供了可能的解决方案。鉴于知识图谱具有克服这些障碍的潜力,本文提出了一种通过资源描述框架语言在知识图谱中表达古生物知识的实用方法。通过深入研究钙质纳米化石生物带的结构化数据(UC带、CC带和NC带),提出了描述古生物生物带和物种的语义单位和逻辑关系的本体,并整合非结构化研究报告中的相关物种记录,构建了多源古生物数据和知识重构相结合的钙质纳米化石知识图谱。我们的重点在于详细介绍构建古生物学知识图谱的技术方面。结果表明,知识图谱可以整合各种来源的半结构化和非结构化古生物数据。本工作旨在帮助古生物学家构建和利用知识图谱,作为未来古生物学知识推理的初步努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
期刊最新文献
From Points to Field Scale: A Decade of Soil-Moisture Monitoring in a German Deciduous Forest (2014–2024) A Data Library of Liquid Clouds Modelled With a Large Eddy Simulation Framework Operational Convection-Permitting COSMO/ICON Ensemble Predictions at Observation Sites (CIENS) Early Instrumental Weather Observations From Ukraine: The ClimUAsd-Stn.v2 Dataset, 1808–1880 A Deep Learning Dataset for Pre-Drill Geohazard Assessment in Taranaki Basin New Zealand
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1