Datasetpublic

OneScience-Group/oc20

OC20 Dataset Description The OC20 dataset is an extxyz subset of the Open Catalyst 2020 (OC20) S2EF (Structure to Energy and Forces) dataset. It contains atomic coordinates, unit-cell information, energies, and forces for adsorption configurations on catalytic material surfaces. Its energy and force fields are consistent with those in the UMA OC20 configuration, making it a standard benchmark dataset for developing and validating machine-learned interatomic… See the full description on the dataset page: https://huggingface.co/datasets/OneScience-Group/oc20.

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

0likes54downloads

Dataset Card

OC20

Dataset Description

The OC20 dataset is an extxyz subset of the Open Catalyst 2020 (OC20) S2EF (Structure to Energy and Forces) dataset. It contains atomic coordinates, unit-cell information, energies, and forces for adsorption configurations on catalytic material surfaces. Its energy and force fields are consistent with those in the UMA OC20 configuration, making it a standard benchmark dataset for developing and validating machine-learned interatomic potential methods for catalytic materials.

This repository currently contains two splits:

—s2ef_200k_uncompressed: Training subset with 2 shards and 10,000 frames in total, with 8–221 atoms per frame.
—s2ef_val_id_uncompressed: In-distribution validation subset with 4 shards and 20,000 frames in total, with 8–223 atoms per frame.

The original data comes from the Open Catalyst Project / fair-chem OC20. This repository provides the accompanying data package for the OneScience UMA fine-tuning example.

The current data package contains approximately 8 files totaling approximately 1.2 GB.

Supported Tasks

This standardized data repository organizes the complete OC20 S2EF subset package, including training and validation sets, to support:

—Fine-tuning machine-learned interatomic potentials on adsorption configurations at catalytic material surfaces
—Training and validation of energy and force prediction models
—Functional testing and benchmark evaluation of the UMA framework

Dataset Format and Structure

The data files are located in the data/oc20/ directory and organized into shards by split:

File Path	Format	Shape / Content	Description
`oc20/s2ef_200k_uncompressed/0.extxyz`	extxyz	`[N_frames, N_atoms]`	Training subset shard 0, 5,000 frames
`oc20/s2ef_200k_uncompressed/1.extxyz`	extxyz	`[N_frames, N_atoms]`	Training subset shard 1, 5,000 frames
`oc20/s2ef_val_id_uncompressed/0.extxyz`	extxyz	`[N_frames, N_atoms]`	Validation subset shard 0, 5,000 frames
`oc20/s2ef_val_id_uncompressed/1.extxyz`	extxyz	`[N_frames, N_atoms]`	Validation subset shard 1, 5,000 frames
`oc20/s2ef_val_id_uncompressed/2.extxyz`	extxyz	`[N_frames, N_atoms]`	Validation subset shard 2, 5,000 frames
`oc20/s2ef_val_id_uncompressed/3.extxyz`	extxyz	`[N_frames, N_atoms]`	Validation subset shard 3, 5,000 frames
`metadata/schema.yaml`	YAML	Data structure description	extxyz field schema definition
`metadata/sha256_manifest.txt`	SHA256	Checksum manifest	File integrity verification

extxyz Data Format

Each configuration consists of an atom-count line, a comment line, and atom lines. The comment line contains Lattice, Properties, energy, free_energy, and pbc. Each atom line contains the element, coordinates, move_mask, tags, and forces.

Field	Type	Shape	Description
`species`	str	`[N_atoms]`	Element symbols spanning various metals and nonmetals
`pos`	float	`[N_atoms, 3]`	Atomic coordinates in Å
`move_mask`	bool	`[N_atoms]`	Whether each atom can move, `T` or `F`
`tags`	int	`[N_atoms]`	Atomic labels distinguishing adsorbates, surfaces, subsurfaces, and other categories
`forces`	float	`[N_atoms, 3]`	Atomic forces in eV/Å
`energy`	float	`[1]`	Total configuration energy in eV
`free_energy`	float	`[1]`	Configuration free energy in eV
`pbc`	bool	`[3]`	Periodic boundary conditions
`Lattice`	float	`[3, 3]`	Periodic cell matrix

How to Use the Dataset

Download the Dataset

bash

hf download OneScience-Group/oc20 --repo-type dataset

Official OneScience Information

Platform	OneScience Main Repository	Skills Repository
Gitee	https://gitee.com/onescience-ai/onescience	https://gitee.com/onescience-ai/oneskills
GitHub	https://github.com/onescience-ai/OneScience	https://github.com/onescience-ai/oneskills

Limitations and License

This dataset is an official S2EF subset of Open Catalyst 2020 (OC20). No new samples were generated, and the original data content was not altered.

—Original source: Open Catalyst Project / fair-chem OC20
—License: Apache License 2.0
—Usage restrictions: Refer to the original OC20 data source and the information provided by the OneScience repository and ModelScope page

When using the OC20 dataset, cite the original Open Catalyst paper:

—Chanussot, L.; Das, A.; Goyal, S.; Lavril, T.; Shuaibi, M.; Riviere, M.; Tran, K.; Heras-Domingo, J.; Ho, C.; Hu, W.; Palizhati, A.; Sriram, A.; Wood, B.; Yoon, J.; Parikh, D.; Zitnick, C. L.; Ulissi, Z. Open Catalyst 2020 (OC20) Dataset and Community Challenges. ACS Catal. 2021, 11 (10), 6059–6072. https://doi.org/10.1021/acscatal.0c04525