datalad
Category: data-science-and-ml · License: MIT · Version: 1.0
Tags: research data management, data versioning, provenance, reproducibility, open science
When to use it
Retrieve, version, and publish scientific datasets with DataLad and git-annex, and capture computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink or a small pointer instead of real data; when an analysis needs a machine-readable record of how each output was produced so it can be re-executed; or when publishing a dataset to siblings such as a GitHub repository plus a storage remote. Also use to decide between DataLad and plain Git for a data-carrying repository.Example requests
Ask your agent in plain language, for example:- “I cloned an OpenNeuro dataset and my script says one of the NIfTI files is ‘not a gzip file’, but ls shows the file is there. What’s going on?”
- “I’m writing up a methods section for a paper. My repo has raw/sub-01_bold.nii.gz (about 2 GB per subject) and a script code/smooth.py that writes derivatives/sub-01_smoothed.nii.gz. I want anyone to be able to re-execute that step later and see exactly which inputs and command produced the output. Second runs of my script currently fail with ‘Permission denied’ on the output file. How should I set this up?”
- “I’ve got a 400 GB imaging dataset I want to share with collaborators. The code goes on GitHub, but the data should sit in an S3 bucket. I want people to be able to clone from GitHub and then pull the actual files without anything breaking. How do I publish it?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole data-science-and-ml category with /plugin install data-science-and-ml@research-agent-skills.