Many research groups aspire to make data and code FAIR and reproducible, yet struggle because the data and code life cycles are disconnected, executable environments are often missing from published work, and technical skill requirements hinder adoption. Existing approaches rarely enable researchers to keep using their preferred tools or support seamless execution across domains. To close this gap, we developed the open-source Reproducible Research Platform (RRP), which unifies research data management with version-controlled, containerized computational environments in modular, shareable projects. RRP enables anyone to execute, reuse, and publish fully documented, FAIR research workflows without manual retrieval or platform-specific setup. We demonstrate RRP's impact by reproducing results from diverse published studies, including work over a decade old, showing sustained reproducibility and usability. With a minimal graphical interface focused on core tasks, modular tool installation, and compatibility with institutional servers or local computers, RRP makes reproducible science broadly accessible across scientific domains.

翻译：许多研究团队致力于使数据与代码符合FAIR原则并具备可复现性，但常因数据与代码生命周期脱节、已发表工作中缺乏可执行环境、以及技术技能门槛阻碍采用而面临困难。现有方案鲜少允许研究人员继续使用其偏好工具，或支持跨领域的无缝执行。为弥合此差距，我们开发了开源可复现研究平台（RRP），该平台将研究数据管理与版本控制、容器化的计算环境统一于模块化、可共享的项目中。RRP使任何人都能执行、复用和发布具备完整文档、符合FAIR原则的研究工作流，无需手动检索或特定平台设置。我们通过复现多项已发表研究（包括十余年前的成果）的结果，展示了RRP的实效，证明了其持续的可复现性与可用性。凭借专注于核心任务的极简图形界面、模块化工具安装、以及与机构服务器或本地计算机的兼容性，RRP使可复现科学广泛适用于各科学领域。