# Dataset Viewer Migration

## Goal

Expose canonical and pre-standard recordings as separate Hub configurations so
users do not mistake metadata-incomplete historical material for canonical
standard data.

## Why this is not applied in v0.2.0

The current repository places canonical MP4 files directly in
`Standard_Time_Lapses/` and supporting provenance holdings beneath
`Standard_Time_Lapses/Provenance/`. A broad `data_dir` configuration could
therefore ingest noncanonical provenance videos.

Hugging Face supports multiple configurations and folder-local video metadata,
but the exact direct-file glob and metadata discovery behavior should be tested
through a Hub pull request before changing the public default configuration.

## Proposed pull-request test

1. Add a folder-local canonical metadata file whose `file_name` values are
   relative to `Standard_Time_Lapses/`.
2. Add a folder-local pre-standard metadata file with explicit
   `collection_tier = pre_standard` and `is_canonical = false`.
3. Add two README configurations:
   - `canonical` — default, direct MP4 files only
   - `pre_standard` — separate historical subset
4. Use a direct-file glob for canonical MP4 files so the `Provenance/` subtree
   is excluded.
5. Confirm the PR preview reports the exact active-index counts, currently 338
   canonical and 129 pre-standard rows, with zero provenance videos and zero
   unindexed direct files.
6. Confirm folder-local metadata is attached to every expected row.
7. Merge only after Viewer and Parquet generation succeed.

## Candidate YAML for PR testing

This block is a test proposal, not the current card configuration:

```yaml
configs:
- config_name: canonical
  default: true
  data_dir: Standard_Time_Lapses
  data_files:
  - split: archive
    path: "*.mp4"
  drop_labels: true
- config_name: pre_standard
  data_dir: Pre_Standard_Time_Lapses
  data_files:
  - split: archive
    path: "*.mp4"
  drop_labels: true
```

If folder-local metadata is not discovered with the direct-file glob, do not
broaden the glob. Instead, create explicit Parquet manifests for the two
configurations so row membership is unambiguous.

## Split terminology

Use `archive` rather than `train` if supported by the Viewer build. Neither
configuration should imply an official machine-learning evaluation split.