Articles | Volume 18, issue 5
https://doi.org/10.5194/essd-18-3671-2026
https://doi.org/10.5194/essd-18-3671-2026
Data description article
 | 
01 Jun 2026
Data description article |  | 01 Jun 2026

OneDZ: a global detrital zircon database and implications for constructing giant geoscience database

Keran Li, Xiumian Hu, Rong Chai, Jianghai Yang, Weiwei Xue, Yingdi Pan, Taiyang Li, Can Fang, Anlin Ma, Hu Huang, Qianqian Guo, Wentao Yang, Lisha Hu, Liang Qi, Guohui Chen, Gaoyuan Sun, Shijie Zhang, Tao Deng, Kuizhou Li, Jiaopeng Sun, and Biao Gao

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2025-157', Anonymous Referee #1, 03 Jul 2025
    • AC1: 'Reply on RC1', Keran Li, 01 Aug 2025
  • AC2: 'Comment on essd-2025-157', Keran Li, 01 Aug 2025
  • RC2: 'Comment on essd-2025-157', Bryant Ware, 05 Aug 2025
    • AC3: 'Reply on RC2', Keran Li, 07 Aug 2025

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Keran Li on behalf of the Authors (22 Oct 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (07 Dec 2025) by Kirsten Elger
RR by Bryant Ware (18 Mar 2026)
ED: Publish subject to minor revisions (review by editor) (20 Mar 2026) by Kirsten Elger
AR by Keran Li on behalf of the Authors (29 Mar 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Reconsider after major revisions (04 Apr 2026) by Kirsten Elger
AR by Keran Li on behalf of the Authors (29 Apr 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (01 May 2026) by Kirsten Elger
AR by Keran Li on behalf of the Authors (04 May 2026)  Manuscript 
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Short summary
OneDZ is a global detrital zircon database comprising 2.7 million uranium-lead and 200 thousand lutetium-hafnium isotopic records. Artificial intelligence, large language model agents, and custom code were employed to develop tools for big data evaluation, enhancing database functionality and offering new insights into managing large-scale unstructured geoscience data.
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