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

Author:

Wang Chengshan12,Hazen Robert M3,Cheng Qiuming4,Stephenson Michael H5,Zhou Chenghu6,Fox Peter7,Shen Shu-zhong8,Oberhänsli Roland9,Hou Zengqian10,Ma Xiaogang11ORCID,Feng Zhiqiang12,Fan Junxuan8,Ma Chao11,Hu Xiumian8,Luo Bin6,Wang Juanle6,Schiffries Craig M13

Affiliation:

1. State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China

2. School of the Earth Science and Resources, China University of Geosciences, Beijing 100083, China

3. Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC 20015, USA

4. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, China

5. British Geological Survey, Nottingham, NG12 5GG, UK

6. State Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing 100101, China

7. Tetherless World Constellation, Rensselaer Polytechnic Institute, Troy, NY 12180, USA

8. School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China

9. Institute of Earth and Environmental Sciences, University of Potsdam, Potsdam 14476, Germany

10. Institute of Geology, Chinese Academy of Geological Sciences, Beijing 100037, China

11. Department of Computer Science, University of Idaho, Moscow, ID 83844, USA

12. Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China

13. DDE Center of Excellence (Suzhou), Kunshan 215300, China

Abstract

Abstract 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.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Oxford University Press (OUP)

Subject

Multidisciplinary

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