AI 中文总结
该研究开发了开源网页环境ARGOS，结合GPU加速渲染与模板驱动方法，可用于宇宙学模拟结果的实时可视分析，支持目录级与对象级探索，还适配SKIRT合成多波段成像数据，源代码与参考部署均已公开。
AI 中文摘要
背景：现代宇宙学模拟依赖复杂假设并生成丰富且高度复杂的数据集，解读其结果以提取新科学见解仍具挑战性。现有可视化工具功能强大，但入门门槛相对较高，且并非以通过实时、直观的可视分析进行知识发现为设计重点，这与生物信息学等其他研究领域形成对比，后者的可视分析工具已深度融入科学发现工作流。目标：我们的目标是补充现有宇宙学可视化工具生态系统，开发一款轻量、用户友好的应用，支持可视分析并将结果无阻碍地传播给科学界。方法：我们开发了ARGOS，这是一个开源的基于网页的实时可视分析环境，专为宇宙学模拟输出量身打造，注重用户体验。ARGOS结合了GPU加速的浏览器渲染，用于交互式探索大型数据集，以及模板驱动的方法，使其能快速适配其他类型的数据和分析工作流。重要的是，ARGOS结合了目录级和对象级探索，允许用户在大量对象集合与单个对象快照之间无缝切换。结果：我们通过多个宇宙学粒子数据集的示例仪表板展示了ARGOS如何支持直观的可视数据探索，并通过SKIRT合成多波段成像数据产品的仪表板说明其更广泛的适用性。源代码在该URL下以MIT许可免费提供，包含示例数据的参考部署在该URL可用。
英文摘要
Context: Modern cosmological simulations rely on sophisticated assumptions and generate rich, highly complex datasets. Interpreting their results in order to extract new scientific insights remains challenging. Existing visualisation tools offer powerful capabilities but often come with a relatively high barrier for entry, and are not designed with a focus on knowledge discovery through real-time, intuitive visual analytics. This stands in contrast to other research domains, such as bioinformatics, where visual analytics tools have become deeply embedded in scientific discovery workflows. Aim: Our goal is to complement the existing ecosystem of cosmological visualisation tools with a lightweight, user-friendly application that supports visual analytics and frictionless dissemination of results to the scientific community. Methods: We developed ARGOS, an open-source, web-based environment for real-time visual analytics, tailored to cosmological simulation outputs and designed with an emphasis on user experience. ARGOS combines GPU-accelerated browser rendering for interactive exploration of large datasets with a template-driven approach that enables rapid adaptation to other types of data and analysis workflows. Importantly, ARGOS combines catalogue-level and object-level exploration, allowing users to move seamlessly from large ensembles of objects to snapshots of individual objects. Results: We demonstrate how ARGOS can support intuitive visual data exploration through example dashboards for multiple cosmological particle datasets, and illustrate broader applicability with dashboards for SKIRT synthetic multi-band imaging data products. Source code is freely available at https://github.com/pvaut/skirt-argos under the MIT licence. A reference deployment, including sample data, is available at https://skirt-argos.ugent.be.
DOI：10.1051/0004-6361/202660853
