We introduce the feasibility of running hybrid analysis pipelines in the REANA reproducible analysis platform. The REANA platform allows researchers to specify declarative computational workflow steps describing the analysis process and to execute analysis workload on remote containerised compute clouds. We have designed an abstract job controller component permitting to execute different parts of the analysis workflow on different compute backends, such as HTCondor, Kubernetes and SLURM. We have prototyped the designed solution including the job execution, job monitoring, and input/output file staging mechanism between the various compute backends. We have tested the prototype using several particle physics model analyses. The present work introduces support for hybrid analysis workflows in the REANA reproducible analysis platform and paves the way towards studying underlying performance advantages and challenges associated with hybrid analysis patterns in complex particle physics data analyses.
In this paper we present the CERN Analysis Preservation service as a FAIR (Findable, Accessible, Interoperable and Reusable) research data preservation repository platform for LHC experiments. The CERN Analysis Preservation repository allows LHC collaborations to deposit and share the structured information about analyses as well as to capture the individual data assets associated to the analysis. We describe the typical data ingestion pipelines, through which an individual physicist can preserve and share their final n-tuples, ROOT macros, Jupyter notebooks, or even their full analysis workflow code and any intermediate datasets of interest for preservation within the restricted context of experimental collaboration. We discuss the importance of annotating the deposited content with high-level structured information about physics concepts in order to promote information discovery and knowledge sharing inside the collaboration. Finally, we describe techniques used to facilitate the reusability of preserved data assets by capturing and re-executing reproducible recipes and computational workflows using the REANA Reusable Analysis platform.
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