数据供应链中基于区块链的问责机制：一种数据物料清单方法
Blockchain-Enabled Accountability in Data Supply Chain: A Data Bill of Materials Approach
AI总结：
针对AI时代数据供应链的可追溯与问责难题，本研究提出DataBOM概念并构建区块链支撑的服务平台，通过元数据记录数据依赖关系，经案例与定量分析验证了方案的可行性与性能。
摘要：
在以GPT-4等大规模生成式模型为标志的先进人工智能时代，确保数据集在整个生命周期中的可追溯性、可验证性和可复现性，对研究机构和科技公司而言至关重要。这些机构越来越依赖海量语料库来训练和微调先进AI模型，由此形成的复杂数据供应链亟需有效的数据治理机制。此外，由于不同利益相关方可能使用各类工具，且往往缺乏充分措施保障数据的问责性和结果的可靠性，这一挑战进一步加剧。本研究将“软件物料清单（Software Bill of Materials）”的概念适配应用于数据治理与管理领域以应对上述挑战，并提出“数据物料清单（Data Bill of Materials，DataBOM）”，通过存储特定元数据来记录不同数据集与利益相关方之间的依赖关系。本文展示了提供基于区块链的DataBOM服务的平台架构，提出了利益相关方的交互协议，并讨论了DataBOM元数据的最低要求。研究分别通过案例研究和定量分析，从可行性和性能两方面对所提方案进行了评估。
英文摘要：
In the era of advanced artificial intelligence, highlighted by large-scale generative models like GPT-4, ensuring the traceability, verifiability, and reproducibility of datasets throughout their lifecycle is paramount for research institutions and technology companies. These organisations increasingly rely on vast corpora to train and fine-tune advanced AI models, resulting in intricate data supply chains that demand effective data governance mechanisms. In addition, the challenge intensifies as diverse stakeholders may use assorted tools, often without adequate measures to ensure the accountability of data and the reliability of outcomes. In this study, we adapt the concept of ``Software Bill of Materials" into the field of data governance and management to address the above challenges, and introduce ``Data Bill of Materials" (DataBOM) to capture the dependency relationship between different datasets and stakeholders by storing specific metadata. We demonstrate a platform architecture for providing blockchain-based DataBOM services, present the interaction protocol for stakeholders, and discuss the minimal requirements for DataBOM metadata. The proposed solution is evaluated in terms of feasibility and performance via case study and quantitative analysis respectively.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
