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Jilong Liu, Zhaoqiang Li, Jianwen Zhou, Qingyu Xiao, Kaixin Yang, Ziru Chen, Lu Yao, Hengshen Liu, Yibo Miao, Junyu Luo, Yiping Chen, Ruifeng jing, Yixue Li

Guangzhou Laboratory, Guangzhou 510005, Guangdong Province, China

Effective management of computational provenance, archiving, and distribution is essential for reproducible biomedical research. While solutions like Workflow Hub and Sapporo support secondary analysis pipelines through Workflow RO-Crate, comprehensive mechanisms for end-to-end biomedical dry-lab analyses—encompassing both secondary (e.g., workflow-based) and tertiary phases (e.g., Jupyter/RStudio-based interpretive analytics)—remain underdeveloped. Bioinformatics cloud platforms (e.g., Terra, Seven Bridges, Bio-OS) leverage workspace structures (termed Projects in Seven Bridges) to organize such analyses, integrating metadata, primary data, analytic workflows, interactive environments (notebooks/RStudio), and execution environments and histories. To bridge this gap, we present Workspace RO-Crate, based on three core profiles defined by the Workflow Run Crate Working Group: Process Run Crate, Workflow Run Crate, and Provenance Run Crate. This enables unified encapsulation of multi-stage computational provenance, dependencies, and environments. Integrated with this specification, we deploy Digger (https://network.miracle.ac.cn/digger), a centralized repository for archiving and sharing Workspace RO-Crate artifacts within Bio-OS ecosystems. This infrastructure supports cross-platform distribution and re-execution of packaged workspaces: Biocomputation objects exported to Digger from any Bio-OS instance platform can be directly imported, reproduced, and extended on others. By standardizing provenance tracking and enabling interoperability across project-scale analytical lifecycles, Workspace RO-Crate and Digger enhance accessibility, reproducibility, and translational impact in computational biomedicine.