Year: 2017
Type: conference-paper
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.
Authors: Kyle Cranmer, Lukas Heinrich
Institution: New York University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
Funder: National Science Foundation
OpenAlex ID: W2622966599