Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction Method
Abstract The rare earth elements Sm and Nd significantly address fundamental questions about crustal growth, such as its spatiotemporal evolution and the interplay between orogenesis and crustal accretion. Their relative immobility during high-grade metamorphism makes the Sm-Nd isotopic system cruci...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04229-5 |
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| author | Zhixin Guo Tao Wang Chaoyang Wang Jianping Zhou Guanjie Zheng Xinbing Wang Chenghu Zhou |
| author_facet | Zhixin Guo Tao Wang Chaoyang Wang Jianping Zhou Guanjie Zheng Xinbing Wang Chenghu Zhou |
| author_sort | Zhixin Guo |
| collection | DOAJ |
| description | Abstract The rare earth elements Sm and Nd significantly address fundamental questions about crustal growth, such as its spatiotemporal evolution and the interplay between orogenesis and crustal accretion. Their relative immobility during high-grade metamorphism makes the Sm-Nd isotopic system crucial for inferring crustal formation times. Historically, data have been disseminated sporadically in the scientific literature due to complicated and costly sampling procedures, resulting in a fragmented knowledge base. However, the scattering of critical geoscience data across multiple publications poses significant challenges regarding human capital and time. In response, we present an automated tabular extraction method for harvesting tabular geoscience data. We collect 10,624 Sm-Nd data entries from 9,138 tables in over 20,000 geoscience publications using this method. We manually selected 2,118 data points from it to supplement the previously constructed global Sm-Nd dataset, increasing its sample count by over 20%. Our automatic data collection methodology enhances the efficiency of data acquisition processes spanning various scientific domains. |
| format | Article |
| id | doaj-art-0229e5f88c5c43948556eced712e1dad |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-0229e5f88c5c43948556eced712e1dad2025-02-09T12:11:40ZengNature PortfolioScientific Data2052-44632025-02-0112111310.1038/s41597-024-04229-5Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction MethodZhixin Guo0Tao Wang1Chaoyang Wang2Jianping Zhou3Guanjie Zheng4Xinbing Wang5Chenghu Zhou6Shanghai Jiao Tong University, School of Electronic Information and Electrical EngineeringChinese Academy of Geological Sciences, Institute of GeologyChinese Academy of Geological Sciences, Institute of GeologyShanghai Jiao Tong University, School of Electronic Information and Electrical EngineeringShanghai Jiao Tong University, John Hopcroft Center for Computer ScienceShanghai Jiao Tong University, School of Electronic Information and Electrical EngineeringChinese Academy of Sciences, Institute of Geological Sciences and Natural Resources ResearchAbstract The rare earth elements Sm and Nd significantly address fundamental questions about crustal growth, such as its spatiotemporal evolution and the interplay between orogenesis and crustal accretion. Their relative immobility during high-grade metamorphism makes the Sm-Nd isotopic system crucial for inferring crustal formation times. Historically, data have been disseminated sporadically in the scientific literature due to complicated and costly sampling procedures, resulting in a fragmented knowledge base. However, the scattering of critical geoscience data across multiple publications poses significant challenges regarding human capital and time. In response, we present an automated tabular extraction method for harvesting tabular geoscience data. We collect 10,624 Sm-Nd data entries from 9,138 tables in over 20,000 geoscience publications using this method. We manually selected 2,118 data points from it to supplement the previously constructed global Sm-Nd dataset, increasing its sample count by over 20%. Our automatic data collection methodology enhances the efficiency of data acquisition processes spanning various scientific domains.https://doi.org/10.1038/s41597-024-04229-5 |
| spellingShingle | Zhixin Guo Tao Wang Chaoyang Wang Jianping Zhou Guanjie Zheng Xinbing Wang Chenghu Zhou Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction Method Scientific Data |
| title | Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction Method |
| title_full | Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction Method |
| title_fullStr | Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction Method |
| title_full_unstemmed | Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction Method |
| title_short | Sm-Nd Isotope Data Compilation from Geoscientific Literature Using an Automated Tabular Extraction Method |
| title_sort | sm nd isotope data compilation from geoscientific literature using an automated tabular extraction method |
| url | https://doi.org/10.1038/s41597-024-04229-5 |
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