Ensuring the trustworthiness and long-term verifiability of scientific data is a foundational challenge in the era of data-intensive, collaborative research. Provenance metadata plays a key role in this context, capturing the origin, transformation, and usage of research artifacts. However, existing solutions often fall short when applied to distributed, multi-institutional settings. This paper introduces a modular, domain-agnostic architecture for provenance tracking in federated environments, leveraging permissioned blockchain infrastructure to guarantee integrity, immutability, and auditability. The system supports decentralized interaction, persistent identifiers for artifact traceability, and a provenance versioning model that preserves the history of updates. Designed to interoperate with diverse scientific domains, the architecture promotes transparency, accountability, and reproducibility across organizational boundaries. Ongoing work focuses on validating the system through a distributed prototype and exploring its performance in collaborative settings.

翻译：在数据密集型协作研究时代，确保科学数据的可信性与长期可验证性是一项基础性挑战。溯源元数据在此背景下发挥着关键作用，它记录了研究产物的来源、转换过程及使用情况。然而，现有解决方案在应用于分布式、多机构协作环境时往往存在不足。本文提出一种面向联邦环境的模块化、领域无关的溯源追踪架构，该架构利用许可区块链基础设施保障数据的完整性、不可篡改性与可审计性。系统支持去中心化交互，为研究产物提供持久标识以实现可追溯性，并通过溯源版本管理模型完整保存更新历史。该架构设计具备跨科学领域的互操作性，旨在提升跨组织边界的透明度、问责制与可复现性。当前工作重点在于通过分布式原型系统进行验证，并探究其在协作环境中的性能表现。