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、地球化学和岩石学的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、岩浆如何从地球内部输送到地表以熔岩形式喷发，以及温度、压力和成分如何影响火山喷发的类型和动态。观察和实验数据对于校准模型和评估模型结果的准确性至关重要。 该项目的重点是将 EarthChem (http://www.earthchem.org) 的数据资源与 ENKI 软件框架 (http://enki-portal.org) 的建模功能集成。 目标是充分整合这两种资源，并将它们作为支持研究和学习的云访问工具提供给科学界。该集成工具将鼓励社区使用数据驱动的建模工具，并通过举办扩大和吸引 ENKI 和 EarthChem 用户群的研讨会，吸引早期职业研究人员更广泛地参与这些领域。另一个目标是开发有助于发布可复制、可再现的建模和数据驱动的研究产品的工作流程。该项目中生成的所有软件都将是开源的。该合作项目的主要目标是将 EarthChem 提供的数据资源与 ENKI 软件框架中的热力学和地球动力学建模功能相集成。目标是开发一个开源、基于容器、支持云、数据驱动的建模平台，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举办研讨会来鼓励使用数据驱动的建模工具，扩大和吸引 ENKI 和 EarthChem 用户群，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程，以可复制和可再现的方式促进结果的传播和出版。 该项目满足了 VGP 研究界的重要且既定的需求。 在ENKI建模框架开发之前，VGP中的建模工具主要是基于应用程序、特定于操作系统的，并且很大程度上依赖于少数研究人员进行修改和更新。 ENKI 通过创建基于 Python 框架的基础设施，实现了 VGP 中模型驱动研究方法的范式转变，该基础设施建立了对底层工具的统一访问，简化了模型校准和维护的过程，并通过使用Jupyter 笔记本和服务器可通过 Web 浏览器作为基于云的资源进行访问。 ENKI 建模环境的缺陷是缺乏持久且维护良好的数据资源，这些数据资源直接支持模型校准、限制对模型使用重要的参数以及提供评估模型预测的方法。 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，支持 VGP 的研究和教育，并鼓励模型使用、建模工作流程和模型发布方面的标准，以更好地实现可复制和可再现的科学。 社区参与是该项目的重要组成部分。三个用户研讨会将以虚拟或面对面的形式进行，目的是吸引早期职业 VGP 研究人员利用 EarthChem-ENKI 平台。该项目中产生的所有软件都将是开源的。这项工作由地球科学理事会和计算机和信息科学与工程理事会高级网络基础设施办公室资助。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查进行评估，被认为值得支持标准。