Supporting data for "File-based localization of numerical perturbations in data analysis pipelines"

Salari, Ali;Kiar, Gregory;Lewis, Lindsay;Evans, Alan, C;Glatard, Tristan

Description

Data analysis pipelines are known to be impacted by computational conditions, presumably due to the creation, propagation, and amplification of numerical errors. While this process could play a major role in the current reproducibility crisis, the precise causes of such instabilities and the path along which they propagate in pipelines are unclear. We present Spot, a tool to identify which processes in a pipeline create numerical differences when executed in different computational conditions. Spot leverages system-call interception through ReproZip to reconstruct and compare provenance graphs without pipeline instrumentation. By applying Spot to the structural pre-processing pipelines of the Human Connectome Project, we found that linear and non-linear registration are the cause of most numerical instabilities in these pipelines, which confirms previous findings.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.5

FAIR Score

31%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

GigaScience Database

License

Creative Commons Zero v1.0 Universal

Assigned Domain

Subfield

Computational Theory and Mathematics

Field

Computer Science

Domain

Physical Sciences

Confidence Score

51%

Source

Scholar Data Model

Keywords

ImagingNeuroscienceSoftware

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00