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The Vera C. Rubin Observatory Data Butler and Pipeline Execution System
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The Rubin Observatory's Data Butler is designed to allow data file location and file formats to be abstracted away from the people writing the science pipeline algorithms. The Butler works in conjunction with the workflow graph builder to allow pipelines to be constructed from the algorithmic tasks. These pipelines can be executed at scale using object stores and multi-node clusters, or on a laptop using a local file system. The Butler and pipeline system are now in daily use during Rubin construction and early operations.
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Cited by 3 Pith papers
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DeepDISC-photoz: Deep Learning-Based Photometric Redshift Estimation for Rubin LSST
DeepDISC photo-z, an instance-segmentation network with a mixture-density redshift head, produces better photometric redshifts than catalog-based BPZ and FlexZBoost on simulated Rubin LSST images.
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Data Movement Model for the Vera C. Rubin Observatory
Rubin Observatory's data movement relies on Rucio and FTS for transfers, plus three custom tools that tie Rucio to the Data Butler registry.
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Implementing SIAv2 Over Rubin Observatory's Data Butler
Rubin Observatory has implemented an SIAv2 image access service that queries the Data Butler directly, with some metadata gaps for coadded images.
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