Yadage and Packtivity – analysis preservation using parametrized workflows

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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