# Overview Biomedical research today frequently involves ad-hoc data-sharing practices that create significant security, privacy, and reproducibility concerns. To address these issues, *Biomedical Decentralized Science* (BioDeSci) proposes leveraging blockchain and decentralized technologies for enhanced collaboration, transparency, and efficiency in scientific discovery. However, effectively adopting these technologies introduces distinct challenges at three interlinked levels: the **data**, **model**, and **evaluation** levels. Each level faces specific privacy, compliance, and operational barriers, motivating the need for advanced privacy-preserving and decentralized solutions.

Status Quo: Fragmented and Insecure Biomedical Data Sharing. Without a secure framework, biomedical institutions often share data manually via email, FTP, or cloud storage services. This results in privacy risks (e.g., exporting raw CSV/JSON/DICOM), lack of auditability and version control, and redundant local data copies. Independent ML pipelines operate in isolation, with no synchronization, verification, or provenance tracking, leading to inconsistency and regulatory overhead

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