Reproducibility
Domain: Data & Datasets
🎯 Motivation
Can someone else get the same results with the same data and code? Essential for scientific credibility.
📋 Concrete Example
Reproducibility: ‘Here is the data (v3), code (v2.1), and random seed (42). Anyone can re-run and get 85.2% accuracy.’ Without reproducibility, results cannot be trusted.
🔗 Analogy
A science experiment - you write the procedure so others can replicate it and get the same result. Reproducibility means others can reproduce your AI results.