| # Deploying the upgraded Hugging Face dataset card |
|
|
| This folder contains drop-in replacements for the metadata files in the |
| [`monteirot/wellbench`](https://huggingface.co/datasets/monteirot/wellbench) |
| dataset repo: |
|
|
| | File | Replaces | |
| |-------------------|---------------------------------------------------------------| |
| | `README.md` | The current 376-byte README that only says "Benchmark data: …"| |
| | `.gitattributes` | The current `.gitattributes` (recommended LFS rules) | |
|
|
| Your existing `croissant.json` (31.9 kB) and the data folders |
| (`synthetic_datasets/`, `CTGAN_synthetic_data/`) are **not** modified. |
|
|
| --- |
|
|
| ## How to upload |
|
|
| ### Option A — Web UI (one file at a time) |
|
|
| 1. Open <https://huggingface.co/datasets/monteirot/wellbench/tree/main>. |
| 2. Click the existing `README.md` → **Edit** (pencil icon) → paste the new |
| contents of `README.md` → **Commit changes**. |
| 3. Repeat for `.gitattributes`. |
|
|
| ### Option B — `huggingface-cli` (recommended for both files at once) |
|
|
| ```bash |
| pip install -U huggingface_hub |
| huggingface-cli login |
| |
| cd huggingface/ # this folder |
| huggingface-cli upload monteirot/wellbench README.md --repo-type dataset |
| huggingface-cli upload monteirot/wellbench .gitattributes --repo-type dataset |
| ``` |
|
|
| ### Option C — Git over HTTPS (full repo flow) |
|
|
| ```bash |
| git lfs install |
| git clone https://huggingface.co/datasets/monteirot/wellbench |
| cd wellbench |
| |
| cp ../huggingface/README.md README.md |
| cp ../huggingface/.gitattributes .gitattributes |
| |
| git add README.md .gitattributes |
| git commit -m "Upgrade dataset card and LFS rules" |
| git push |
| ``` |
|
|
| --- |
|
|
| ## After uploading — verify in this order |
|
|
| 1. **Card YAML parses cleanly.** Refresh |
| <https://huggingface.co/datasets/monteirot/wellbench>. The left rail |
| should now show: |
| - **Tasks:** Tabular Regression · Time Series Forecasting |
| - **Modalities:** Tabular |
| - **Tags:** synthetic-data · synthetic-tabular · well-logs · petrophysics · |
| pore-pressure · ctgan · physics-based · benchmark · neurips · … |
| - **License:** MIT |
| - **Size:** 100K < n < 1M |
| |
| 2. **All six configs appear.** The Dataset Viewer top-bar should show the |
| selector with: `physics_zone_1` (default) · `physics_zone_2` · |
| `physics_zone_3` · `ctgan_zone_1` · `ctgan_zone_2` · `ctgan_zone_3`. |
| Each should expose its three named splits. |
|
|
| 3. **The Viewer renders rows.** Pick `physics_zone_1 / missa_keswal_01` — |
| you should see numerical columns `DEPTH`, `GR`, `DT`, `RHOB`, `RT`, `HP`, |
| `OB`, `DT_NCT`, `PPP`. If column types look wrong, the auto-Parquet |
| conversion needs a re-run; click **Refresh dataset** in the Settings. |
|
|
| 4. **`load_dataset` round-trips.** From a fresh Python: |
| |
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("monteirot/wellbench", "physics_zone_1") |
| print(ds) |
| df = ds["missa_keswal_01"].to_pandas() |
| assert {"DEPTH","GR","DT","RHOB","RT","HP","OB","DT_NCT","PPP"} <= set(df.columns) |
| ``` |
| |
| 5. **Croissant validates.** The Hub auto-generates a Croissant record from |
| the README YAML at the `/croissant` endpoint. Confirm it's well-formed: |
| |
| ```bash |
| pip install "mlcroissant[parquet]" |
| mlcroissant validate \ |
| --jsonld https://huggingface.co/api/datasets/monteirot/wellbench/croissant |
| # exit 0 → ready for the NeurIPS D&B submission requirement |
| ``` |
| |
| Optional: run the same validator on the **manually authored** |
| `croissant.json` you already host: |
| |
| ```bash |
| curl -L https://huggingface.co/datasets/monteirot/wellbench/resolve/main/croissant.json \ |
| -o /tmp/croissant.json |
| mlcroissant validate --jsonld /tmp/croissant.json |
| ``` |
| |
| --- |
| |
| ## Croissant: the two files explained |
| |
| There are now effectively **two** Croissant records for this dataset, and |
| that's fine: |
| |
| | Source | Generated from | Use it for | |
| |-----------------------------------------------------|-----------------------|--------------------------------------------| |
| | `…/api/datasets/monteirot/wellbench/croissant` | README YAML (auto) | Discovery, NeurIPS D&B compliance check | |
| | `…/resolve/main/croissant.json` | Hand-authored | The `mlc.Dataset("croissant.json")` example in your code, custom record sets | |
| |
| **Recommended:** keep both. The auto-generated one is regenerated on every |
| push and always reflects the current YAML; the hand-authored one lets you |
| expose richer record sets (like your `physics-samples` example) that the |
| auto-generator doesn't infer from filenames alone. |
| |
| If the two ever drift in licence, citation, or column types, fix the |
| hand-authored file — reviewers will compare them. |
| |
| --- |
| |
| ## Optional next steps |
| |
| These are not in this folder, but are worth doing before NeurIPS submission: |
| |
| 1. **Add a Croissant-RAI block** to `croissant.json` — `dataLifecycle`, |
| `dataCollection`, `dataPreprocessing`, `dataLimitations`, `dataBiases`, |
| `personalSensitiveInformation`. Use <https://croissant-editor.com/>. |
| |
| 2. **Convert CSVs to Parquet** for the Viewer to run faster and column |
| types to be preserved without inference. Hugging Face will auto-convert |
| on the `refs/convert/parquet` branch, but committing Parquet directly |
| gives you control over schemas and row-group sizes. |
| |
| 3. **Mint a Zenodo DOI** by tagging a release of the GitHub repo and |
| enabling the Zenodo–GitHub integration. Add the DOI to both the GitHub |
| README and the Citation block of this dataset card. |
| |
| 4. **Cross-link**: ensure the Hugging Face dataset card and the GitHub |
| README both link bidirectionally and that the BibTeX entries match. |
| |
