The Square Kilometre Array Observatory (SKAO) faces un- precedented technological challenges due to the vast scale and complexity of its data. This paper provides an overview of research by the AMIGA group to address these computing and reproducibility challenges. We present advancements in semantic data models, analysis services integrated into federated infrastructures, and the application to astronomy studies of techniques that enhance research transparency. By showcasing these astronomy work, we demonstrate that achieving reproducible science in the Big Data era is feasible. However, we conclude that for the SKAO to succeed, the development of the SKA Regional Centre Network (SRCNet) must explicitly incorporate these reproducibility requirements into its fundamental architectural design. Embedding these standards is crucial to enable the global community to conduct verifiable and sustainable research within a federated environment.

翻译：平方公里阵列天文台（SKAO）因其数据的巨大规模和复杂性面临着前所未有的技术挑战。本文概述了AMIGA研究组为应对这些计算与可重现性挑战所开展的研究工作。我们展示了语义数据模型、集成到联邦基础设施中的分析服务，以及提升研究透明度的技术在天文学研究中的应用进展。通过展示这些天文研究工作，我们证明在大数据时代实现可重现科学是可行的。然而，我们得出结论：为使SKAO取得成功，SKA区域中心网络（SRCNet）的构建必须将这些可重现性要求明确纳入其基础架构设计之中。将这些标准嵌入系统对于全球科研共同体在联邦化环境中开展可验证且可持续的研究至关重要。