So, I’ve been using the term “data hygiene” for the measures we take in (safety) ML to keep test and training data separate. Stuff like

• test data on access controlled network share
• acquiring the test set later and by different teams
• Thresholdout (when I finally get the chance to play around with it)

But apparently, I just read that term in some fringe paper once and actually data hygiene is a separate concept in data science?!

Does anyone got a good term for the methods/approaches?