EarthCube Data Infrastructure: Intelligent Databases and Analysis Tools for Geospace Data

EarthCube数据基础设施：地理空间数据的智能数据库和分析工具

• 批准号: 1639683
• 负责人: Alexander Kosovichev
• 金额: $ 50万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1639683&HistoricalAwards=false
• 关键词: EarthCube; Data; Infrastructure; Intelligent; Databases

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

太阳活动和变化是决定地球状态的关键因素之一。美国大气，全球趋势和气候变化。高能辐射和物质抛射形式的爆炸事件会在电离层和磁层引起地磁风暴，影响生物系统，扰乱电网和通信。研究地球系统与空间环境和太阳变率的耦合是理解和预测地球系统复杂演化的关键。为了促进关于太阳影响的跨学科研究，PI和小组将开发一个独特的数据环境，将整合新的和存档的卫星和地面观测数据。综合数据环境将允许研究人员有效地访问太阳和地球空间数据，并将它们用于研究太阳活动和变化及其对地球系统的影响的基本问题，以及开发新的预测能力。由太阳物理学家和计算机科学家合作开发的用于构建智能综合数据库的创新跨学科方法，将有助于地球立方体和相关领域的知识发现。拟议的活动将有助于将创新的数据分析、数据可视化和数据驱动的建模技术转移到本科和研究生的课堂教学中，并转移到可能受益于类似框架的其他研究领域。主要目标是开发用于数据访问和分析的工具，这些工具可以被地球科学社区轻松地用于研究和建模耦合地球系统的各种组件。该项目将开发创新工具，提取和分析现有的观测和建模数据，以便采用新的基于物理和机器学习的方法来理解和预测太阳活动及其对地球空间和地球系统的影响。地球空间数据丰富：每天获得数tb的太阳和空间观测数据。从众多航天器和地面数据档案中寻找相关信息并加以利用是一项至关重要的任务，目前也是一项艰巨的任务。该项目的范围是开发和评估数据集成工具，以满足两类太阳物理数据的通用数据访问和发现需求：1)长期天气活动和变率，以及2)极端地球有效太阳事件。该项目将整合现有的数据资源，如太阳物理知识数据库（HEK）、太阳动力学观测台联合科学操作中心（SDO JSOC）、虚拟太阳观测台（VSO）、太阳物理综合观测台（HELIO）等。该方法包括开发数据集成基础设施和访问方法，能够1)自动搜索和识别由空间和地面天文台产生的图像模式和事件数据记录，2)自动关联并行多波长/多仪器数据库条目与唯一模式或事件标识符。3)自动检索这些数据记录和管道处理，以便根据可从补充数据源推断的一组预定义的物理参数对每个模式或事件进行注释；4)生成模式或目录以及相关的用户友好图形界面工具，这些工具能够提供快速搜索、快速预览和自动数据检索功能

项目成果

Statistical Properties of Soft X-Ray Emission of Solar Flares

• DOI: 10.3847/1538-4357/ab06c3
• 发表时间: 2018-10
• 期刊: The Astrophysical Journal
• 作者: V. Sadykov;A. Kosovichev;I. Kitiashvili;A. Frolov

Dressing the Coronal Magnetic Extrapolations of Active Regions with a Parameterized Thermal Structure

• DOI: 10.3847/1538-4357/aaa4bf
• 发表时间: 2018-01
• 期刊: The Astrophysical Journal
• 作者: G. Nita;N. Viall;J. Klimchuk;M. Loukitcheva;D. Gary;A. Kuznetsov;G. Fleishman

Intelligent Databases and Machine-Learning Analysis Tools for Heliophysics

太阳物理学智能数据库和机器学习分析工具

• DOI: 10.6084/m9.figshare.14848713.v1
• 发表时间: 2021
• 期刊: 2021 EarthCube Annual Meeting
• 作者: Kosovichev, A.;Sadykov, V.;Nita, G.;Oria, V.;Illarionov, E.;Tlatov, A.
• 通讯作者: Tlatov, A.

Revealing the Evolution of Non-thermal Electrons in Solar Flares Using 3D Modeling

使用 3D 建模揭示太阳耀斑中非热电子的演化

• DOI: 10.3847/1538-4357/aabae9
• 发表时间: 2018
• 期刊: The Astrophysical Journal
• 作者: Fleishman, Gregory D.;Nita, Gelu M.;Kuroda, Natsuha;Jia, Sabina;Tong, Kevin;Wen, Richard R.;Zhizhuo, Zhou
• 通讯作者: Zhizhuo, Zhou

Statistical Study of Chromospheric Evaporation in Impulsive Phase of Solar Flares

• DOI: 10.3847/1538-4357/aaf6b0
• 发表时间: 2018-05
• 期刊: The Astrophysical Journal
• 作者: V. Sadykov;A. Kosovichev;I. Sharykin;G. Kerr