The next generation of mobile networks, 6G, is expected to enable data-driven services at unprecedented scale and complexity, with stringent requirements for trust, interoperability, and automation. Central to this vision is the ability to create, manage, and share high-quality datasets across distributed and heterogeneous environments. This paper presents the data architecture of the 6G-DALI project, which implements a federated dataspace and DataOps infrastructure to support secure, compliant, and scalable data sharing for AI-driven experimentation and service orchestration. Drawing from principles defined by GAIA-X and the International Data Spaces Association (IDSA), the architecture incorporates components such as federated identity management, policy-based data contracts, and automated data pipelines. We detail how the 6G-DALI architecture aligns with and extends GAIA-X and IDSA reference models to meet the unique demands of 6G networks, including low-latency edge processing, dynamic trust management, and cross-domain federation. A comparative analysis highlights both convergence points and necessary innovations.

翻译：下一代移动网络6G有望以前所未有的规模和复杂性实现数据驱动服务，并对信任、互操作性和自动化提出严格要求。实现这一愿景的核心在于能够在分布式异构环境中创建、管理和共享高质量数据集。本文介绍了6G-DALI项目的数据架构，该架构通过实现联邦数据空间和DataOps基础设施，为AI驱动的实验与服务编排提供安全、合规且可扩展的数据共享支持。该架构借鉴GAIA-X与国际数据空间协会（IDSA）定义的原则，整合了联邦身份管理、基于策略的数据合约及自动化数据流水线等组件。我们详细阐述了6G-DALI架构如何与GAIA-X和IDSA参考模型对齐并扩展，以满足6G网络的独特需求，包括低延迟边缘处理、动态信任管理和跨域联邦。通过对比分析，本文揭示了架构的共性特征与必要的创新点。