Yadage and Packtivity - analysis preservation using parametrized workflows release_aim7gvk56vfmpjzend242jdzvi

by Kyle Cranmer, Lukas Heinrich

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2017  

Abstract

Preserving data analyses produced by the collaborations at LHC in a parametrized fashion is crucial in order to maintain reproducibility and re-usability. We argue for a declarative description in terms of individual processing steps - packtivities - linked through a dynamic directed acyclic graph (DAG) and present an initial set of JSON schemas for such a description and an implementation - yadage - capable of executing workflows of analysis preserved via Linux containers.
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Date   2017-06-06
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arXiv  1706.01878v1
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Revision: 4d8f60f4-215e-47d5-a552-9c330ae424c6
API URL: JSON