3. Human Review & Cleanup

The curatorial step that transforms machine‑clean metadata into library‑grade truth

Once the metadata has been extracted (Step 1) and normalized (Step 2), the next phase is the most important one in the entire workflow: human review. This is where the machine’s best guesses are checked, corrected, clarified, and elevated into a clean, authoritative dataset.

The scripts can repair encoding, normalize punctuation, and extract primary composers — but they cannot interpret ambiguous titles, resolve conflicting metadata, or understand historical context. That’s where human judgment comes in.

This step produces the final, curated metadata file that the renamer script will use to generate deterministic filenames and rewrite internal MIDI metadata.

What You’re Working With

You will be editing:

normalized_metadata.xlsx

This file contains:

  • filename
  • title
  • composer
  • primary_composer
  • comments
  • tempo
  • time_signature
  • key_signature

Every row corresponds to one MIDI file.

Your job is to turn this into the canonical metadata for the entire library.

What to Look For During Review

Below are the most common issues you’ll encounter and how to fix them.

1. Incorrect or incomplete titles

Examples:

  • “Long Way Tipperary” → “It’s a Long Way to Tipperary”
  • “SabreDance” → “Sabre Dance”
  • “Unknown Title” → look up the correct name if possible

Best practice: 
Use the most widely recognized title, not the filename’s guess.

2. Multiple or ambiguous composers

Examples:

  • “Smith / Jones” → choose the primary composer
  • “Traditional / Arr. X” → composer = “Traditional”, comments = “Arr. X”
  • “Unknown” → leave blank or mark as “Traditional” if appropriate

Best practice: 
Composer should reflect authorship, not arrangement.

3. Medleys and multi‑part works

Examples:

  • “Disney Medley”
  • “Beatles Medley (Part 1)”
  • “Star Wars Suite”

Best practice: 
Keep the title exactly as you want it to appear in the final filename.
If the medley has a known canonical name, use it.

4. Encoding artifacts the normalizer couldn’t fix

Examples:

  • “François” → “François”
  • “It’s” → “It’s”

Best practice: 
Correct these manually — the renamer will preserve your edits.

5. Comments that belong elsewhere

Sometimes comments contain:

  • arranger names
  • performance notes
  • copyright info
  • leftover text events

Best practice: 
Move arranger names to comments, not composer.
Remove junk text entirely.

6. Missing metadata

If a row is missing:

  • composer
  • title
  • comments

…fill in what you can.

Best practice: 
If you cannot determine the composer, leave it blank — the renamer handles this gracefully.

General Best Practices

Be consistent

If you choose “Traditional” for folk tunes, use it everywhere.
If you prefer “arr. X” in comments, use that format consistently.

Use proper capitalization

The renamer does not change capitalization — what you write is what you get.

Avoid punctuation that normalizes poorly

Characters like /, ?, :, and * will be stripped or replaced.
Prefer simple ASCII punctuation.

Keep titles human‑readable

The renamer will normalize filenames, not titles.
Titles should look good in a catalog.

Don’t worry about filename formatting

The renamer handles:

  • underscores
  • double dashes
  • normalization
  • collision avoidance

You only need to provide clean metadata.

When You’re Done

When the spreadsheet is fully reviewed and corrected, save it as:

normalized_metadata_edit.xlsx

or export as:

normalized_metadata_edit.csv

This curated file becomes the authoritative source of truth for Step 4: the renaming pass.

Summary

The Human Review & Cleanup step is where the library becomes yours.
It’s the moment where machine‑generated guesses are replaced with curated, historically accurate, musically meaningful metadata. This curated file ensures that the final filenames — and the internal MIDI metadata — reflect the true identity of each piece.

Once this step is complete, the renamer script can safely and deterministically transform the entire library into a clean, consistent, future‑proof collection.

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