Datasets:

cparidaAI
/

fair_dataset_demo

id stringclasses 3 values	formula stringclasses 3 values	system stringclasses 1 value	bandgap_eV float64 3.2 5.6	structure_path stringclasses 3 values
ABO3_0001	SrTiO3	perovskite	3.2	data/structures/ABO3_0001.xyz
ABO3_0002	BaZrO3	perovskite	5	data/structures/ABO3_0002.xyz
ABO3_0003	LaAlO3	perovskite	5.6	data/structures/ABO3_0003.xyz

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.

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

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:

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

Findable: metadata, tags, README, (add DOI later via Zenodo)
Accessible: public repo, open formats
Interoperable: CSV/JSON/EXTXYZ, schema describes fields/units
Reusable: license, clear citation, validation, examples

Downloads last month: 43

Size of downloaded dataset files:

405 Bytes

Size of the auto-converted Parquet files:

2.87 kB

Number of rows:

AI4Materials Demo FAIR Perovskites

Contents

Provenance

How to load

License

F.A.I.R. checklist