Collaborative Research: EarthCube Data Capabilities: A data-driven modeling infrastructure to support research and education in volcanology, geochemistry and petrology

协作研究：EarthCube 数据功能：数据驱动的建模基础设施，支持火山学、地球化学和岩石学的研究和教育

• 批准号: 2026916
• 负责人: Kerstin Lehnert
• 金额: $ 45.33万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026916&HistoricalAwards=false
• 关键词: Collaborative; Research; EarthCube; Data; Capabilities

Research and education in volcanology, geochemistry, and petrology rely on data-driven modeling tools. Modeling helps us to understand the conditions under which rocks form, how magmas are transported from the Earth's interior to erupt as lavas at the surface, and how temperature, pressure, and composition affect the style and dynamics of volcanic eruptions. Observational and experimental data are essential to calibrating models and to evaluating the veracity of model outcomes. This project focuses on integrating data resources at EarthChem (http://www.earthchem.org) with the modeling capabilities of the ENKI software framework (http://enki-portal.org). The objective is to fully integrate these two resources and to make them available to the scientific community as cloud-accessible tools that support both research and learning. The integrated tool will encourage community usage of data-driven modeling tools and entrain broader participation of early career researchers in these fields by conducting workshops that expand and engage the ENKI and EarthChem user base. Another goal is to develop workflows that help to publish replicable, reproducible modeling and data-driven research products. All software produced in this project will be open source.This collaborative project has the principal objective of integrating data resources available at EarthChem with thermodynamic and geodynamic modeling capabilities found in the ENKI software framework. The goal is to develop an open-source, container-based and cloud-enabled, data-driven modeling platform to support research and education for the volcanology, geochemistry, and petrology (VGP) community. An equally important objective is to encourage usage of data-driven modeling tools by conducting workshops that expand and engage the ENKI and EarthChem user base and encourage participation of early career researchers in the VGP community. The data analysis and modeling frameworks will support research workflows that facilitate dissemination and publication of results in a manner that is both replicable and reproducible. The project addresses an important and established need of the VGP research community. Previous to the development of the ENKI modeling framework, modeling tools in VGP were principally app-based, operating system-specific, and largely dependent on a small number of researchers for modification and updates. ENKI enabled a paradigm shift in the approach to model-driven research in VGP by creating an infrastructure based on Python frameworks that establish uniform access to underlying tools, streamline the process of model calibration and maintenance, and facilitate platform-independent access by the use of Jupyter notebooks and servers that are accessed as cloud-based resources with a web browser. A deficiency of the ENKI modeling environment is the absence of persistent and well-maintained data resources that directly support model calibration, that constrain parameters important for model usage, and that provide means of evaluating model predictions. The EarthChem data systems contain data that provide these constraints. Integration of EarthChem and ENKI will deliver a robust modeling ecosystem that supports research and education in VGP, and encourages standards in model usage, modeling workflows, and model publication that better enable replicable and reproducible science. Community engagement is a crucial component of the project. Three user workshops will be conducted in a virtual or in person format with the aim of engaging early career VGP researchers in utilizing the EarthChem-ENKI platform. All software produced in this project will be open source. This work is funded by the Directorate for Geosciences and the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

火山学，地球化学和质学研究和教育依赖于数据驱动的建模工具。建模有助于我们了解岩石形成的条件，岩浆如何从地球内的熔岩中传输到地面爆发，以及温度，压力和成分如何影响火山喷发的样式和动态。观察和实验数据对于校准模型和评估模型结果的真实性至关重要。 该项目着重于将Earthchem（http://www.earthchem.org）与ENKI软件框架（http://enki-portal.org）的建模功能集成在一起的数据资源。 目的是将这两个资源充分整合，并使科学界作为支持研究和学习的云访问工具。该集成工具将通过开展扩展和参与Enki和Earthchem用户群的研讨会来鼓励社区使用数据驱动的建模工具，并吸引早期职业研究人员在这些领域的更广泛参与。另一个目标是开发有助于发布可复制，可重复的建模和数据驱动的研究产品的工作流程。该项目中生产的所有软件都将是开源。该协作项目的主要目标是将Earthchem的可用数据资源与ENKI软件框架中的热力学和地球动力学建模功能相结合。目的是开发一个开源，基于容器和云的数据驱动建模平台，以支持火山学，地球化学和岩石学（VGP）社区的研究和教育。 同样重要的目标是通过开展扩展和参与Enki和Earthchem用户群的研讨会来鼓励使用数据驱动的建模工具，并鼓励早期职业研究人员参与VGP社区。数据分析和建模框架将支持研究工作流，这些工作流以可复制和可重现的方式促进结果的传播和发布。 该项目解决了VGP研究社区的重要且确定的需求。 在开发ENKI建模框架之前，VGP中的建模工具主要基于应用程序，特定于操作系统，并且很大程度上取决于少数用于修改和更新的研究人员。 Enki通过建立基于Python框架的基础架构来建立统一访问基础工具，简化模型校准和维护的过程，并通过使用Jupyter Notebooks and Ersers来促进与基于Web brows的cloud Browser访问云的browser的范围，从而促进了对基础工具的统一访问，从而使模型驱动的研究的方法范围转变为VGP的模型驱动研究。 ENKI建模环境的不足是缺乏直接支持模型校准的持久且维护良好的数据资源，这限制了对模型使用重要的参数，并且提供了评估模型预测的手段。 Earthchem数据系统包含提供这些约束的数据。 Earthchem和Enki的整合将提供一个强大的建模生态系统，以支持VGP研究和教育，并鼓励模型使用，建模工作流和模型出版物的标准，以更好地启用可复制和可重复的科学。 社区参与是该项目的关键组成部分。将以虚拟或以个人形式进行三个用户研讨会，以吸引早期职业VGP研究人员利用Earthchem-enki平台。该项目中生产的所有软件将是开源。这项工作由地球科学局和计算机和信息科学与工程局的高级网络基础设施办公室资助。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准通过评估来进行评估的。