Community-curated Galaxy interfaces with the Galaxy Labs Engine.

IF 5 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES
Cameron J Hyde, Anna Syme, Bérénice Batut, Paul F Zierep, Winnie Mok, Wendi A Bacon, Gareth R Price
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引用次数: 0

Abstract

The Galaxy platform is a globally distributed environment for data-intensive research, providing thousands of analysis tools across major public servers. However, this decentralized ecosystem presents usability challenges for both users and administrators, particularly in surfacing relevant tools and workflows for specific communities. To improve discoverability and support global collaboration, the Galaxy project has employed community-driven "Galaxy Flavours"-subdomains with curated content for defined research domains. While conceptually valuable, Flavours suffer from critical limitations: They are statically deployed, difficult to replicate across servers, and often provide inconsistent and unintuitive user interfaces. To address these challenges, we developed the Galaxy Labs Engine (GLE), a service that enables the creation of Galaxy Labs. This new paradigm enables globally synchronized, domain-specific entry points built from structured, reusable web content. GLE separates content from deployment, allowing communities to define a shared canonical representation of their domain, while enabling individual Galaxy servers to locally customize presentation. Labs are designed to guide users through curated tools, workflows, and training resources, and are aimed at researchers who are new to the analytical methods or technologies specific to the domain. The GLE provides a consistent, customizable, and community-driven interface layer for the Galaxy ecosystem. By fostering FAIR principles, labs offer a scalable improvement to Flavours and enhance Galaxy's ability to support diverse research communities. GLE is open-source and currently deployed at https://labs.usegalaxy.org.au, with multiple Labs already supporting active user groups. This work strengthens Galaxy's role as a collaborative platform for reproducible, user-centred science.

社区策划的银河接口与银河实验室引擎。
Galaxy平台是用于数据密集型研究的全球分布式环境,在主要公共服务器上提供数千种分析工具。然而,这种分散的生态系统对用户和管理员都提出了可用性挑战,特别是在为特定社区提供相关工具和工作流程方面。为了提高可发现性和支持全球合作,银河项目采用了社区驱动的“银河风味”——为定义的研究领域策划内容的子域。虽然在概念上很有价值,但flavor受到了严重的限制:它们是静态部署的,难以跨服务器复制,并且经常提供不一致且不直观的用户界面。为了应对这些挑战,我们开发了Galaxy Labs Engine (GLE),这是一项能够创建Galaxy Labs的服务。这个新范例支持从结构化的、可重用的web内容构建全局同步的、特定于领域的入口点。GLE将内容与部署分离开来,允许社区定义其域的共享规范表示,同时使各个Galaxy服务器能够本地自定义表示。实验室的设计目的是通过精心策划的工具、工作流程和培训资源来指导用户,并针对那些对特定领域的分析方法或技术不熟悉的研究人员。银河实验室引擎为银河生态系统提供了一个一致的、可定制的、社区驱动的接口层。通过培养公平原则,实验室提供了可扩展的改进口味,增强了银河支持多样化研究社区的能力。GLE是开源的,目前部署在https://labs.usegalaxy.org.au上,多个实验室已经支持活跃的用户组。这项工作加强了银河作为可重复的、以用户为中心的科学合作平台的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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