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Best practices for version control of research datasets, not just code
Method Help
Researchers usually version‑control code but often forget datasets. Data evolves through cleaning and processing steps, and version mismatches can break reproducibility. What conventions help you track dataset versions properly?
Donald Thomas, Dennis Campbell and 23 others4 Comments-
Keep raw data separate from any processed or cleaned versions from day one.
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Record every transformation step so intermediate versions stay traceable.
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Use descriptive version names that reflect what changed between data versions.
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Store a checksum or hash for each dataset version to detect silent corruption.
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