  In Non-Terrestrial Networks (NTN), achieving effective radio resource
allocation across multi-satellite system, encompassing efficient channel and
bandwidth allocation, effective beam management, power control and interference
mitigation, poses significant challenges due to the varying satellite links and
highly dynamic nature of user traffic. This calls for the development of an
intelligent decision-making controller using Artificial Intelligence (AI) to
efficiently manage resources in this complex environment. In this context, open
datasets can play a crucial role in driving new advancement and facilitating
research. Recognizing the significance, this paper aims to contribute the
satellite communication research community by providing various open datasets
that incorporate realistic traffic flow enabling a variety of uses cases. The
primary objective of sharing these datasets is to facilitate the development
and benchmarking of advanced resource management solutions, thereby improving
the overall satellite communication systems. Furthermore, an application
example focused on beam placement optimization via terminal clustering is
provided. This assists in optimizing beam allocation task, enabling adaptive
beamforming to effectively meet spatiotemporally varying user traffic demands
and optimize resource utilization.
