| 项目编号: | 1639683
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| 项目名称: | EarthCube Data Infrastructure: Intelligent Databases and Analysis Tools for Geospace Data |
| 作者: | Alexander Kosovichev
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| 承担单位: | New Jersey Institute of Technology
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| 批准年: | 2017
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| 开始日期: | 2017-08-15
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| 结束日期: | 2019-07-31
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| 资助金额: | 500000
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Geosciences - Integrative and Collaborative Education and Research
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| 英文关键词: | heliophysics knowledge database
; data-driven modeling technique
; parallel multi-wavelength/multi-instrument database entry
; geospace datum
; user-friendly graphical interface tool
; datum integration tool
; innovative data analysis
; earth system
; data integration infrastructure
; intelligent integrated database
; innovative tool
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| 英文摘要: | Solar activity and variability are among the key factors determining the state of the Earth?s atmosphere, global trends and climate changes. Explosive events in the form of high-energy radiation and mass ejections cause geomagnetic storms in the ionosphere and magnetosphere, affecting biological systems, disrupting power grids, and communications. For understanding and predicting the complex and evolving Earth system, it is critical to investigate its coupling to the space environment and to solar variability. To facilitate interdisciplinary research on solar influences, PI and the team will develop a unique data environment that will integrate new and archived satellite and ground-based observational data. The integrated data environment will allow researchers to efficiently access solar and geospace data and use them for studying fundamental problems of solar activity and variability and their impacts on Earth systems, as well as for developing new predictive capabilities. The innovative interdisciplinary approach for building an intelligent integrated database, developed in collaboration between heliophysicists and computer scientists, will contribute to knowledge discovery in the EarthCube and associated fields. The proposed activities will facilitate the transfer of innovative data analysis, data visualization, and data-driven modeling techniques to in-class teaching at the undergraduate and graduate levels and to other fields of research that may benefit from a similar framework.
The primary goal is to develop tools for data access and analysis that can be easily used by the Geoscience community for studying and modeling various components of the coupled Earth system. The project will develop innovative tools to extract and analyze the available observational and modeling data in order to enable new physics-based and machine-learning approaches for understanding and predicting solar activity and its influence on the geospace and Earth systems. The geospace data are abundant: several terabytes of solar and space observations are obtained every day. Finding the relevant information from numerous spacecraft and ground-based data archives and using it is a paramount, and currently a difficult task.
The scope of the project is to develop and evaluate data integration tools to meet common data access and discovery needs for two types of Heliophysics data: 1) long-term synoptic activity and variability, and 2) extreme geoeffective solar events. The project will integrate existing data resources, such as the Heliophysics Knowledge Database (HEK), Solar Dynamics Observatory Joint Science Operations Center (SDO JSOC), Virtual Solar Observatory (VSO), Heliophysics Integrated Observatory (HELIO), and others.
The methodology consists in the development of a data integration infrastructure and access methods capable of 1) automatic search and identification of image patterns and event data records produced by space and ground-based observatories, 2) automatic association of parallel multi-wavelength/multi-instrument database entries with unique pattern or event identifiers, 3) automatic retrieval of such data records and pipeline processing for the purpose of annotating each pattern or event according to a predefined set of physical parameters inferable from complimentary data sources, and 4) generation of a pattern or catalog and associated user-friendly graphical interface tools that are capable to provide fast search, quick preview, and automatic data retrieval capabilities |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/89350
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
Alexander Kosovichev. EarthCube Data Infrastructure: Intelligent Databases and Analysis Tools for Geospace Data. 2017-01-01.
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