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data-driven discovery: A New Era of Exploiting the Literature and data

Journal of data and Information Science 2016年第4期1卷 1-9页

作者： Ying Ding Kyle Stirling Department of Information and Library Science Indiana University

In the current data-intensive era, the traditional hands-on method of conducting scientific research by exploring related publications to generate a testable hypothesis is well on its way of becoming obsolete within just a year or two. Analyzing the literature and data to automatically generate a hypothesis might become the de facto approach to inform the core research efforts of those trying to master the exponentially rapid expansion of publications and datasets. Here, viewpoints are provided and discussed to help the understanding of challenges of data-driven discovery.

关键词： A New Era of Exploiting the Literature and data data-driven discovery

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

引用

National Science Review 2021年第9期8卷 156-166页

作者： Chengshan Wang Robert M.Hazen Qiuming Cheng Michael H.Stephenson Chenghu Zhou Peter Fox Shu-zhong Shen Roland Oberhansli Zengqian Hou Xiaogang Ma Zhiqiang Feng Junxuan Fan Chao Ma Xiumian Hu Bin Luo Juanle Wang Craig M.Schiffries State Key Laboratory of Biogeology and Environmental Geology China University of Geosciences School of the Earth Science and Resources China University of Geosciences Earth and Planets Laboratory Carnegie Institution for Science State Key Laboratory of Geological Processes and Mineral Resources China University of Geosciences British Geological Survey State Key Laboratory of Resources and Environment Information System Institute of Geographical Science and Natural Resources Chinese Academy of Sciences Tetherless World Constellation Rensselaer Polytechnic Institute School of Earth Sciences and Engineering Nanjing University Institute of Earth and Environmental Sciences University of Potsdam Institute of Geology Chinese Academy of Geological Sciences Department of Computer Science University of Idaho Petroleum Exploration and Production Research Institute SINOPEC DDE Center of Excellence(Suzhou)

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.

关键词： Deep-Time Digital Earth data-driven discovery big data Earth evolution cyberinfrastructure

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