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Yadage and Packtivity - analysis preservation using parametrized
workflows
release_aim7gvk56vfmpjzend242jdzvi
by
Kyle Cranmer, Lukas Heinrich
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as a article
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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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1706.01878v1
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