| | --- |
| | task_categories: |
| | - tabular-regression |
| | language: |
| | - en |
| | tags: |
| | - physics |
| | - chemistry |
| | - materials |
| | - ASE |
| | - Perovskites |
| | pretty_name: AI4Materials Demo FAIR Perovskites |
| | license: mit |
| | --- |
| | |
| | # AI4Materials Demo FAIR Perovskites |
| |
|
| | This is a **teaching** dataset demonstrating F.A.I.R. hosting on the Hugging Face Hub. |
| | It contains a small table of oxide perovskites with band gaps and toy EXTXYZ structures. |
| |
|
| | ## Contents |
| | - `data/table.csv` — main tabular data |
| | - `data/records.jsonl` — line-delimited JSON mirror |
| | - `data/structures/*.xyz` — example structures (EXTXYZ) |
| | - `metadata/schema.json` — JSON Schema for validation |
| | - `CITATION.cff`, `LICENSE` — citation & reuse terms |
| |
|
| | ## Provenance |
| | Synthetic examples generated for classroom demonstration on {datetime.utcnow().date()}. |
| |
|
| | ## How to load |
| | ```python |
| | from datasets import load_dataset |
| | ds = load_dataset("cparidaAI/fair_dataset_demo", data_files={"train": "data/table.csv"}) |
| | print(ds) |
| | ``` |
| | Or download a structure file: |
| | ```python |
| | from huggingface_hub import hf_hub_download |
| | path = hf_hub_download(repo_id="cparidaAI/fair_dataset_demo", filename="data/structures/ABO3_0001.xyz") |
| | ``` |
| |
|
| | ## License |
| | MIT. Please cite using `CITATION.cff`. |
| |
|
| | ## F.A.I.R. checklist |
| | - **F**indable: metadata, tags, README, (add DOI later via Zenodo) |
| | - **A**ccessible: public repo, open formats |
| | - **I**nteroperable: CSV/JSON/EXTXYZ, schema describes fields/units |
| | - **R**eusable: license, clear citation, validation, examples |
| |
|
