A practical approach to building a calcareous nannofossil knowledge graph

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Hongyi Zhao, Bin Hu, Chao Ma, Shijun Jiang, Yi Zhang, Xin Li, Lirong Chen, Can Cai, Longgang Ye, Shengjian Zhou, Chengshan Wang
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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

构建钙质化石知识图谱的实用方法
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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.
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