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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.
Afiliación
  • Wang C; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China.
  • Hazen RM; Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC 20015, USA.
  • Cheng Q; State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, China.
  • Stephenson MH; BritishGeological Survey, Nottingham, NG12 5GG, UK.
  • Zhou C; State Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing 100101, China.
  • Fox P; Tetherless World Constellation, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
  • Shen SZ; School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China.
  • Oberhänsli R; Institute of Earth and Environmental Sciences, University of Potsdam, Potsdam 14476, Germany.
  • Hou Z; Institute of Geology, Chinese Academy of Geological Sciences, Beijing 100037, China.
  • Ma X; Department of Computer Science, University of Idaho, Moscow, ID 83844, USA.
  • Feng Z; Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China.
  • Fan J; School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China.
  • Ma C; Department of Computer Science, University of Idaho, Moscow, ID 83844, USA.
  • Hu X; School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China.
  • Luo B; State Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing 100101, China.
  • Wang J; State Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing 100101, China.
  • Schiffries CM; DDE Center of Excellence (Suzhou), Kunshan 215300, China.
Natl Sci Rev ; 8(9): nwab027, 2021 Sep.
Article en En | MEDLINE | ID: mdl-34691735
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Natl Sci Rev Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Natl Sci Rev Año: 2021 Tipo del documento: Article País de afiliación: China