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The Deep-Time Digital Earth program: data-driven discovery in geosciences

Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databa...

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Autores principales: Wang, Chengshan, Hazen, Robert M, Cheng, Qiuming, Stephenson, Michael H, Zhou, Chenghu, Fox, Peter, Shen, Shu-zhong, Oberhänsli, Roland, Hou, Zengqian, Ma, Xiaogang, Feng, Zhiqiang, Fan, Junxuan, Ma, Chao, Hu, Xiumian, Luo, Bin, Wang, Juanle, Schiffries, Craig M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433093/
https://www.ncbi.nlm.nih.gov/pubmed/34691735
http://dx.doi.org/10.1093/nsr/nwab027
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author Wang, Chengshan
Hazen, Robert M
Cheng, Qiuming
Stephenson, Michael H
Zhou, Chenghu
Fox, Peter
Shen, Shu-zhong
Oberhänsli, Roland
Hou, Zengqian
Ma, Xiaogang
Feng, Zhiqiang
Fan, Junxuan
Ma, Chao
Hu, Xiumian
Luo, Bin
Wang, Juanle
Schiffries, Craig M
author_facet Wang, Chengshan
Hazen, Robert M
Cheng, Qiuming
Stephenson, Michael H
Zhou, Chenghu
Fox, Peter
Shen, Shu-zhong
Oberhänsli, Roland
Hou, Zengqian
Ma, Xiaogang
Feng, Zhiqiang
Fan, Junxuan
Ma, Chao
Hu, Xiumian
Luo, Bin
Wang, Juanle
Schiffries, Craig M
author_sort Wang, Chengshan
collection PubMed
description Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE’s mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth's evolution.
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spelling pubmed-84330932021-10-21 The Deep-Time Digital Earth program: data-driven discovery in geosciences Wang, Chengshan Hazen, Robert M Cheng, Qiuming Stephenson, Michael H Zhou, Chenghu Fox, Peter Shen, Shu-zhong Oberhänsli, Roland Hou, Zengqian Ma, Xiaogang Feng, Zhiqiang Fan, Junxuan Ma, Chao Hu, Xiumian Luo, Bin Wang, Juanle Schiffries, Craig M Natl Sci Rev Review Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE’s mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth's evolution. Oxford University Press 2021-02-11 /pmc/articles/PMC8433093/ /pubmed/34691735 http://dx.doi.org/10.1093/nsr/nwab027 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Wang, Chengshan
Hazen, Robert M
Cheng, Qiuming
Stephenson, Michael H
Zhou, Chenghu
Fox, Peter
Shen, Shu-zhong
Oberhänsli, Roland
Hou, Zengqian
Ma, Xiaogang
Feng, Zhiqiang
Fan, Junxuan
Ma, Chao
Hu, Xiumian
Luo, Bin
Wang, Juanle
Schiffries, Craig M
The Deep-Time Digital Earth program: data-driven discovery in geosciences
title The Deep-Time Digital Earth program: data-driven discovery in geosciences
title_full The Deep-Time Digital Earth program: data-driven discovery in geosciences
title_fullStr The Deep-Time Digital Earth program: data-driven discovery in geosciences
title_full_unstemmed The Deep-Time Digital Earth program: data-driven discovery in geosciences
title_short The Deep-Time Digital Earth program: data-driven discovery in geosciences
title_sort deep-time digital earth program: data-driven discovery in geosciences
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433093/
https://www.ncbi.nlm.nih.gov/pubmed/34691735
http://dx.doi.org/10.1093/nsr/nwab027
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