@@ -19,9 +19,10 @@ BIDS App Bootstrap (BABS) is a reproducible, generalizable, and
1919scalable Python package for BIDS App analysis of large datasets.
2020It uses `DataLad <https://www.datalad.org/ >`_ and adopts
2121the `FAIRly big framework <https://doi.org/10.1038/s41597-022-01163-2 >`_.
22- Currently it is compatible with SGE and Slurm clusters.
22+ Currently, BABS supports jobs submissions and audits on Sun Grid Engine (SGE) and Slurm
23+ high performance computing (HPC) clusters.
2324
24- BABS functions
25+ BABS programs
2526---------------------
2627
2728.. image :: https://github.com/PennLINC/babs/raw/main/docs/source/_static/babs_cli.png
@@ -32,3 +33,19 @@ Schematic of BABS workflow
3233----------------------------
3334.. image :: https://github.com/PennLINC/babs/raw/main/docs/source/_static/babs_workflow.png
3435.. Note: this image is taken from the main branch, so it's normal that docs built from branches is not up-to-date.
36+
37+ Background and Significance
38+ -------------------------------
39+
40+ Neuroimaging research faces a crisis of reproducibility.
41+ With massive sample sizes and greater data complexity, this problem becomes more acute.
42+ The BIDS Apps - the software operating on BIDS data - have provided a substantial advance.
43+ However, even using BIDS Apps, a full audit trail of data processing is a necessary prerequisite for fully reproducible research.
44+ Obtaining a faithful record of the audit trail is challenging - especially for large datasets.
45+ Recently, the `FAIRly big framework <https://doi.org/10.1038/s41597-022-01163-2 >`_
46+ was introduced as a way to facilitate reproducible processing of large-scale data
47+ by leveraging `DataLad <https://www.datalad.org/ >`_ - a version control system for data management.
48+ However, the current implementation of this framework remains challenging to general users.
49+
50+ BABS was developed to address these challenges
51+ and to facilitate the reproducible application of BIDS Apps to large-scale datasets.
0 commit comments