Supporting Better Insights of Data Science Pipelines with Fine-grained Provenance

Fuente: arXiv

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Bibliographic Details
Main Authors:	Chapman, Adriane, Lauro, Luca, Missier, Paolo, Torlone, Riccardo
Format:	Preprint
Published:	2023
Subjects:	Databases 68 H.1; H.2
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2310.18079