Connecting Minds Around Cloud-Native Research Infrastructure

Do you still see researchers downloading large datasets to their laptops before starting analysis? Despite the availability of cloud platforms and large online datasets, this remains common practice in many research fields. But what is holding us back from more efficient, cloud-native approaches? In this open discussion you will exchange experiences with others who support research infrastructures and digital research practices in the Netherlands. Together you will explore what is needed to make cloud-native data access and processing easier and more widely adopted across research domains. You will discuss questions such as: What technical, organisational or skills barriers still prevent researchers from using cloud-native workflows? Where are the biggest gaps in infrastructure, training, standards or coordination? How can community-driven initiatives be supported by institutions and national infrastructures? You will work together to identify concrete challenges, needs and opportunities. The goal is to produce a shared list of priorities and possible next steps for the Dutch research ecosystem. The discussion builds on experiences from recent national initiatives exploring cloud-native research infrastructures, but the focus will be broader: connecting insights across disciplines and institutions. If you work on research support, digital infrastructure, data services or policy, this session offers a chance to compare perspectives and help shape future approaches for more efficient research workflows. Cloud-native data access and processing are becoming essential capabilities for modern research, particularly as datasets grow larger and more complex. However, many researchers in the Netherlands still rely on inefficient download-and-process workflows due to gaps in infrastructure, standards, training, and coordination. This proposed session connects directly to the CLOUD-NES project, funded by NWO through TDCC-NES, which explores cloud-native data access and processing for the Natural and Engineering Sciences. The project develops a proof-of-concept infrastructure, benchmarks, and training materials to demonstrate the benefits of bringing computation closer to data.