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Ontology Dynamics in a Data Life Cycle: Challenges and Recommendations from a Geoscience Perspective

Journal of Earth Science 2014年第2期25卷 407-412页

作者： Xiaogang Ma peter fox Eric Rozell Patrick West Stephan Zednik Tetherless World Constellation School of Science Rensselaer Polytechnic Institute

Ontologies are increasingly deployed as a computer-accessible representation of key semantics in various parts of a data life cycle and, thus, ontology dynamics may pose challenges to data management and re-use. By using examples in the field of geosciences, we analyze challenges raised by ontology dynamics, such as heavy reworking of data, semantic heterogeneity among data providers and users, and error propagation in cross-discipline data discovery and re-use. We also make recommendations to address these challenges：（1） communities of practice on ontologies to re- duce inconsistency and duplicated efforts; （2） use ontologies in the procedure of data collection and make them accessible to data users; and （3） seek methods to speed up the reworking of data in a Semantic Web context.

关键词： semantic web knowledge evolution data transformation geoscience.

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Disruption in Biogeosciences:Conceptual,Methodological,Digital,and Technological

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Acta Geologica Sinica(English Edition) 2019年第S1期93卷 17-18页

作者： peter fox Tetherless World Constellation Rensselaer Polytechnic InstituteTroyNY 12180USA

Over four years ago,a group of investigators came together to determine if Big Data approaches(specifically data mining,machine learning and analytics in general)might provide insight into some of the grand challenges in Earth’s history:evolution of minerals,rise of oxygen,life,influence of super continental cycles,quantifying the magnitude of extinction events,and *** a result,the team of mineralogists,petrologists,geochemists.

关键词： mineral ecology mineral evolution fossil networks mass extinctions network analytics visual analytics

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激光直接重熔硼铁粉末的组织与性能

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激光杂志 2005年第4期26卷 82-83页

作者：陈先朝 Jiwei-Xie peter fox 广东工业大学材料与能源学院广东广州510643 利物浦大学工程系英国利物浦L69 3GH

运用激光直接重熔法进行快速原型制造,在纯铁粉末中加入硼,考察了不同含硼量及激光扫描工艺参数对试样组织与性能的影响。结果表明,随着硼含量的增加,试样组织的凝固颗粒尺寸增大而球化倾向降低,试样的表面粗糙度变差;但不同激光扫描工... 详细信息

运用激光直接重熔法进行快速原型制造,在纯铁粉末中加入硼,考察了不同含硼量及激光扫描工艺参数对试样组织与性能的影响。结果表明,随着硼含量的增加,试样组织的凝固颗粒尺寸增大而球化倾向降低,试样的表面粗糙度变差;但不同激光扫描工艺参数则影响不大。

关键词：激光直接重熔硼铁粉末组织性能

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

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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 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) 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

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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