Speaker
Description
Bridging the gap between FAIR (Findable, Accessible, Interoperable, Reusable) data availability and its effective use remains a central challenge in data-intensive research. PUNCH4NFDI addresses this challenge through an integrated approach combining federated infrastructure, data platforms, and community-oriented training. Within this framework, Göttingen contributes by connecting technical developments with user-facing services, training, and Open Science activities.
In PUNCH4NFDI (PUNCH-1.0), Göttingen developed and operated the EXPLORE platform, an open-access compute infrastructure deployed at the GoeGrid infrastructure that enables scalable and reproducible analysis of LHC Open Data. EXPLORE integrates dynamic resource provisioning (HTCondor, COBalD/TARDIS) and containerised environments, allowing users to execute full analysis workflows without local setup or collaboration membership. The platform has been successfully used in training and outreach contexts, enabling students, educators, and researchers to perform hands-on analyses on real data, thereby lowering barriers to FAIR data reuse and supporting inclusive access to research infrastructures.
These activities highlight a central lesson: the availability of FAIR data alone is not sufficient-effective reuse requires accessible infrastructure, executable workflows, and structured training. In PUNCH-1.0, these elements were developed and connected in practice through infrastructures such as Compute4PUNCH and REANA, emerging data platform components, and training and outreach activities including the PUNCH Young Academy.
Building on these results, the proposed PUNCH-2.0 project (start October 2026) will extend and formalise this integrated approach through the coordinated interplay of federated compute services, workflow and data integration via the Science Data Platform, and training and community engagement. Göttingen will contribute through the integration of HPC resources (WP1.3), the development of advanced use cases such as EXPLORE 2.0 (WP2.4), and the continued expansion of training and mentoring activities.
This contribution presents both concrete achievements and a forward-looking strategy, demonstrating how the tight integration of infrastructure, workflows, and training can enable the practical and scalable adoption of FAIR data principles.