Collaborative Research: GEO OSE Track 1: Transforming Volcanology towards Open Science in the Cloud with VICTOR

该项目继续开发和扩展VICTOR项目，即火山学计算工具和资源基础设施，该项目为火山学社区提供了一种新的网络基础设施。火山学界正在转变为一门精通计算机、数据驱动的定量学科，这需要一个匹配的网络基础设施。具体来说，VICTOR提供了一个执行火山过程数值模拟的平台，包括熔岩流、火山灰、火山碎片扩散和火山碎屑密度流。在之前的试验阶段，启动了VICTOR平台，并开发了一套初步的代码和工作流程。新项目将通过与社区中的模型和数据库开发人员合作，将这些工具连接到平台上，从而扩展VICTOR的功能。VICTOR的中心目的是促进火山学建模社区提高模型质量和获取，促进模型素养和整体合作。因此，这个项目将特别强调教育和培训。该项目将采取多方面的方法，包括：(1)社区软件代码的包容和整合，(2)研讨会，(3)教育工作者培训和本科和研究生课程的教学模块，以及(4)建立社区治理结构和有效的沟通渠道。VICTOR是基于一个JupyterHub平台，并通过一个中央门户网站访问。所有组件都基于云，以支持基于需求的资源管理、工作流可移植性和再现性，并为更广泛的社区提供对高性能计算的访问。该项目将开发计算工作流程，使用新的功能和模型库来简化模型验证、验证和基准测试，并使用公共应用程序编程接口（api）简化对所需外部数据集（如地形和环境条件）的访问。工作流将利用现代计算工具，如Jupyter Notebooks，最大限度地减少了定位、安装、运行和测试模型的耗时步骤。工作流程将使模型输入和输出标准化，促进对关联和多灾害情景的研究。建模过程的再现性和可靠性将通过保存、重新运行、编辑和测试工作流的能力得到增强。最终，开放获取模型、数据科学工具和提供的低门槛计算资源的组合将提高社区的可用性，并加速向开放科学文化的过渡。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project continues the development and expansion of Project VICTOR, the Volcanology Infrastructure for Computational Tools and Resources, which provides a novel cyberinfrastructure serving the volcanology community. The volcanology community is transforming into a computer-savvy, data-driven, quantitative discipline that requires a matching cyberinfrastructure. Specifically, VICTOR provides a platform for executing numerical simulations of volcanic processes, including lava flows, ash, tephra dispersal, and pyroclastic density currents. During the preceding pilot phase, the VICTOR platform was initiated and a preliminary set of codes and workflows was developed. The new project will expand upon VICTOR capabilities by collaborating with model and database developers in the community to connect these tools to the platform. The central purpose of VICTOR is to catalyze the volcanology modeling community to advance model quality and access and promote model literacy and overall collaboration. Thus, this project will put special emphasis on education and training. The project will take a multi-faceted approach that combines: (1) inclusion and integration of community software codes, (2) workshops, (3) educator training and teaching modules for undergraduate and graduate level classes, and (4) establishment of a community governance structure and effective communication channels.VICTOR is based on a JupyterHub platform, and access is through a central web portal. All components are based in the cloud, to allow for demand-based resource management, workflow portability, and reproducibility, and to offer access to high-performance computing to a broader community. The project will develop computational workflows that use new capabilities and libraries of models to simplify model verification, validation, and benchmarking and streamline access to required external datasets such as topography and environmental conditions using public Application Programming Interfaces (APIs). Workflows will utilize modern computing tools such as Jupyter Notebooks, minimizing the time-intensive steps of locating, installing, running, and testing models. Workflows will enable standardization of model inputs and outputs, facilitating studies of linked- and multi-hazard scenarios. The reproducibility and reliability of the modeling process will be enhanced through capabilities to save, re-run, edit, and test workflows. Ultimately, the combination of open-access models, data science tools, and the provisioned low-barrier access to computing resources will increase usability by the community and accelerate the transition to a culture of open science.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.