Collaborative Research: SI2-SSI: Inquiry-Focused Volumetric Data Analysis Across Scientific Domains: Sustaining and Expanding the yt Community

合作研究：SI2-SSI：跨科学领域以调查为中心的体积数据分析：维持和扩展 yt 社区

• 批准号: 1663954
• 负责人: Leigh Orf
• 金额: $ 27.7万
• 依托单位: University of Wisconsin-Madison
• 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: 2017-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1663954&HistoricalAwards=false
• 关键词: Collaborative; Research; SI2; SSI; Inquiry

Scientific discovery across the physical sciences is increasingly dependent on the analysis of volumetric - or three-dimensional - data, that may come from a supercomputer simulation, direct measurement, or mathematical models. Researchers typically seek to extract meaningful insights from this data by visualizing and analyzing it in various ways. The ways in which scientists process volumetric data are actually quite similar across domains, but cross-disciplinary knowledge transfer and tool development is blocked by barriers of terminology. This project seeks to enhance an analysis and visualization toolkit named yt that is currently primarily used for astrophysical simulations. yt allows scientists to access and analyze data at several different levels by providing an interface that is designed to answer questions motivated by the underlying scientific problem, while worrying less about details such data formats, specific analysis techniques etc. yt's utilization in computational astrophysics has dramatically increased access to advanced algorithms for both visualization and analysis, and fostered the growth of a community of researchers sharing techniques and results. This project seeks to make yt available and adopted by scientists in other domains of science thus reproducing its success in astrophysics in these other science domains. This project will expand the yt community beyond theoretical astrophysics and enable and promote collaboration and advanced data analysis in the fields of meteorology, seismology and global tomography, observational astronomy, hydrology and oceanography, and plasma physics. Improvements to the yt project will proceed along four principal technical avenues. The first is to develop a system that adapts the way yt presents data via a set of domain contexts that encode the ontology, domain-specific vocabulary, and common analysis tasks for a given field of study. This will include creating a domain context system as well as a set of five pilot domain contexts developed in collaboration with domain practitioners. The second is to overhaul the yt field system, adding more versatility and enabling significant optimizations. Thirdly, the project team will implement non-spatial indexing schemes, providing methods for accessing and analyzing data that is not organized according to the standard spatial axes. The final improvement will be the development of a non-local analysis system, allowing generalized path traversal as well as domain convolutions. To ensure wide dissemination and use of these improved capabilities, the team will design domain-specific documentation and training materials, and organize outreach and training events for early-career researchers. This will consist of both hands-on technical workshops and curricula developed in collaboration with Data Carpentry for utilization at other institutions. This combination of technical developments and social investments has been designed to ensure both readiness of the software and engagement of the targeted research communities.

物理科学中的科学发现越来越依赖于对体积数据或三维数据的分析，这些数据可能来自超级计算机模拟、直接测量或数学模型。研究人员通常通过以各种方式可视化和分析这些数据来寻求从这些数据中提取有意义的见解。科学家处理体积数据的方式实际上在各个领域是非常相似的，但跨学科的知识转移和工具开发因术语障碍而受阻。该项目旨在增强一个名为yt的分析和可视化工具包，该工具包目前主要用于天体物理模拟。YT允许科学家在几个不同的层次访问和分析数据，方法是提供一个旨在回答潜在科学问题的界面，同时减少对数据格式、具体分析技术等细节的担忧。YT在计算天体物理学中的应用极大地增加了对用于可视化和分析的高级算法的访问，并促进了共享技术和结果的研究人员社区的发展。该项目力求使yT可供其他科学领域的科学家使用和采用，从而在这些其他科学领域复制其在天体物理学方面的成功。这一项目将使yt社区超越理论天体物理学，并促进和促进气象学、地震学和全球层析、观测天文学、水文学和海洋学以及等离子体物理等领域的合作和高级数据分析。Yt项目的改进将沿着四个主要的技术途径进行。第一个是开发一个系统，以适应yt通过一组领域上下文呈现数据的方式，这些领域上下文对给定研究领域的本体、特定于领域的词汇和常见分析任务进行编码。这将包括创建一个领域背景系统，以及与领域从业者合作开发的一套五个试点领域背景。第二个是彻底改革yt外地系统，增加更多的通用性，并实现显著的优化。第三，项目组将实施非空间索引计划，提供访问和分析不按标准空间轴组织的数据的方法。最后的改进将是开发一个非局部分析系统，允许广义路径遍历以及域卷积。为了确保广泛传播和使用这些改进的能力，该小组将设计特定领域的文件和培训材料，并为职业生涯早期的研究人员组织外联和培训活动。这将包括实际操作技术讲习班和与数据木工合作编制的课程，供其他机构使用。技术开发和社会投资的这种组合旨在确保软件的准备就绪和目标研究社区的参与。

项目成果

Modeling the World’s Most Violent Thunderstorms

模拟世界上最猛烈的雷暴

• DOI: 10.1109/mcse.2021.3069771
• 发表时间: 2021
• 期刊: Computing in Science & Engineering
• 影响因子: 2.1
• 作者: Orf, Leigh

VAPOR: A Visualization Package Tailored to Analyze Simulation Data in Earth System Science

• DOI: 10.3390/atmos10090488
• 发表时间: 2019-07
• 期刊: Atmosphere
• 影响因子: 2.9
• 作者: Shaomeng Li;Stanislaw Jaroszynski;S. Pearse;Leigh Orf;J. Clyne

A Violently Tornadic Supercell Thunderstorm Simulation Spanning a Quarter-Trillion Grid Volumes: Computational Challenges, I/O Framework, and Visualizations of Tornadogenesis

• DOI: 10.3390/atmos10100578
• 发表时间: 2019-09
• 期刊: Atmosphere
• 影响因子: 2.9
• 作者: Leigh Orf

Hydraulic jump dynamics above supercell thunderstorms

• DOI: 10.1126/science.abh3857
• 发表时间: 2021-09-10
• 期刊: SCIENCE
• 影响因子: 56.9
• 作者: O'Neill, Morgan E.;Orf, Leigh;Halbert, Kelton
• 通讯作者: Halbert, Kelton

Tracking the Centre of Asymmetric Vortices Using Wind Velocity Vector Data Fields

• DOI: 10.1007/s10546-022-00739-0
• 发表时间: 2022-09
• 期刊: Boundary-Layer Meteorology
• 影响因子: 4.3
• 作者: Niall Bannigan;Leigh Orf;E. Savory