Data discovery, analysis and reproducibility in Virtual Research Environments (2503.02483v1)

Abstract: During the ESCAPE project, a pilot analysis facility was developed with a bottom-up approach, in collaboration with all the project partners. As a result, the CERN Virtual Research Environment (VRE) initiative proposes a workspace that facilitates data access from the ESCAPE Data Lake, managed by Rucio, a data management framework, and supports interactive analysis via Jupyter notebooks. The facility offers custom software stacks and access to CVMFS, and connects to local data processing resources through REANA, an open-source framework developed by CERN IT for reanalysis and reproducibility. The CERN VRE deploys an instance of REANA, allowing users to utilise its features together with the analysis facility's services. Integrating heterogeneous services with a unified interface significantly eases the user experience. Furthermore, in line with the ESCAPE Open Collaboration, the development of open source tools that can be leveraged by different physics communities with similar analysis strategies, laying the foundation of common lifecycle analysis practices. Therefore, in order to foster accessibility, as well as interactivity, reproducibility and data preservation to more complex infrastructure services, the development of user-friendly middleware should be prioritized. This contribution focuses on the connection of REANA and Zenodo to the CERN Virtual Research Environment's interface through Jupyter extensions. The development of these extensions makes it possible to use the Virtual Research Environment as a single workspace to enhance the lifecycle of research analysis: from data discovery and data access, through interactive analysis and offload to computing resources, to reproducibility and preservation of results.