Dataset Open Access
Tahmasbi, Hossein;
Knüpfer, Andreas;
Kühne, Thomas Dae-Song;
Mir Hosseini, Seyed Hossein
{
"created": "2026-04-10T09:15:24.898416+00:00",
"links": {
"badge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.4596.svg",
"doi": "https://doi.org/10.14278/rodare.4596",
"conceptbadge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.4595.svg",
"conceptdoi": "https://doi.org/10.14278/rodare.4595",
"bucket": "https://rodare.hzdr.de/api/files/8f232daa-8c06-4cf1-a212-e5504add827f",
"html": "https://rodare.hzdr.de/record/4596",
"latest": "https://rodare.hzdr.de/api/records/4596",
"latest_html": "https://rodare.hzdr.de/record/4596"
},
"conceptdoi": "10.14278/rodare.4595",
"conceptrecid": "4595",
"updated": "2026-07-29T14:40:32.204894+00:00",
"files": [
{
"type": "gz",
"links": {
"self": "https://rodare.hzdr.de/api/files/8f232daa-8c06-4cf1-a212-e5504add827f/Unary_Benchmark.tar.gz"
},
"bucket": "8f232daa-8c06-4cf1-a212-e5504add827f",
"size": 13795417,
"key": "Unary_Benchmark.tar.gz",
"checksum": "md5:1ea5cc0b010ef998c4c90800cb995e60"
}
],
"stats": {
"volume": 303499174.0,
"unique_downloads": 18.0,
"version_unique_downloads": 18.0,
"unique_views": 265.0,
"downloads": 22.0,
"version_unique_views": 265.0,
"version_views": 282.0,
"version_downloads": 22.0,
"version_volume": 303499174.0,
"views": 282.0
},
"doi": "10.14278/rodare.4596",
"owners": [
839
],
"metadata": {
"description": "<p>Reference data and scripts generated for\u00a0the \"Benchmarking Universal Machine Learning Interatomic<br>\r\nPotentials on Elemental Systems\" manuscript.</p>",
"access_right_category": "success",
"doi": "10.14278/rodare.4596",
"doc_id": "1",
"related_identifiers": [
{
"relation": "isIdenticalTo",
"identifier": "https://www.hzdr.de/publications/Publ-43234",
"scheme": "url"
},
{
"relation": "isReferencedBy",
"identifier": "https://www.hzdr.de/publications/Publ-43706",
"scheme": "url"
},
{
"relation": "isVersionOf",
"identifier": "10.14278/rodare.4595",
"scheme": "doi"
}
],
"publication_date": "2026-04-09",
"relations": {
"version": [
{
"last_child": {
"pid_type": "recid",
"pid_value": "4596"
},
"index": 0,
"count": 1,
"parent": {
"pid_type": "recid",
"pid_value": "4595"
},
"is_last": true
}
]
},
"license": {
"id": "CC-BY-4.0"
},
"keywords": [],
"title": "Data publication: Benchmarking Universal Machine Learning Interatomic Potentials on Elemental Systems",
"communities": [
{
"id": "matter"
},
{
"id": "rodare"
}
],
"access_right": "open",
"creators": [
{
"orcid": "0000-0002-3072-8217",
"name": "Tahmasbi, Hossein"
},
{
"orcid": "0000-0003-3591-397X",
"name": "Kn\u00fcpfer, Andreas"
},
{
"orcid": "0000-0001-5471-2407",
"name": "K\u00fchne, Thomas Dae-Song"
},
{
"name": "Mir Hosseini, Seyed Hossein"
}
],
"pub_id": "43234",
"resource_type": {
"type": "dataset",
"title": "Dataset"
}
},
"id": 4596,
"revision": 11
}
| All versions | This version | |
|---|---|---|
| Views | 282 | 282 |
| Downloads | 22 | 22 |
| Data volume | 303.5 MB | 303.5 MB |
| Unique views | 265 | 265 |
| Unique downloads | 18 | 18 |