Altar：从早期探索到发表的可共享实验数据结构化
Altar: Structuring Sharable Experimental Data from Early Exploration to Publication
AI总结：
Altar是一个轻量级框架，用于从项目初期开始结构化实验数据，支持灵活的数据存储和可追溯性，促进可重复性和FAIR数据共享。
摘要：
在实验项目活跃发展阶段管理数据和元数据是一项重大挑战，尤其是在协作研究中。这一阶段经常被忽视在项目提案中的数据管理计划中，尽管其在确保可重复性和防止发表时需要回溯重建方面起着重要作用。本文介绍了Altar，一个轻量级、领域无关的框架，用于从项目开始就对实验数据进行结构化处理，而无需施加严格的数据库模型。Altar围绕Sacred实验跟踪模型构建，并捕获实验（元）数据并对其进行结构化。参数、元数据、曲线和小文件存储在一个灵活的NoSQL数据库中，而大型原始数据则存放在专用存储中并通过唯一标识符链接，以确保效率和可追溯性。这种集成可以与现有的工作流组合，允许在最小干扰工作习惯的情况下进行整合。我们根据用户技能水平（博士生、博士后、项目负责人、实验室管理员、系统管理员）记录了使用Altar的不同路径。虽然使用Altar入门不需要专门的基础设施，但该框架可以轻松部署在服务器上，并在扩大规模或准备发表数据时公开访问。通过解决研究的动态阶段，Altar为探索性实验和FAIR对齐的数据共享提供了实用的桥梁。
英文摘要：
Managing the data and metadata during the active development phase of an experimental project presents a significant challenge, particularly in collaborative research. This phase is frequently overlooked in Data Management Plans included in project proposals, despite its important role in ensuring reproducibility and preventing the need for retroactive reconstruction at the time of publication. Here we present Altar, a lightweight, domain-agnostic framework for structuring experimental data from the onset of a project without imposing rigid data models. Altar is built around the Sacred experiment-tracking model and captures experimental (meta)data and structures them. Parameters, metadata, curves and small files are stored in a flexible NoSQL database, while large raw data are maintained in dedicated storage and linked through unique identifiers, ensuring efficiency and traceability. This integration is composable with exiting workflows, allowing integration with minimial disruption of work habits. We document different pathways to use Altar based on users skillset (PhD students, Post-docs, Principal Investigators, Laboratory administrators, System administrators). While getting started with Altar does not require a specialized infrastructure, the framework can be easily deployed on a server and made publicly accessible when scaling up or preparing data for publication. By addressing the dynamic phase of research, Altar provides a practical bridge between exploratory experimentation and FAIR-aligned data sharing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
