October 1, 2021 Dataset Open Access

Fiedler, Lenz; Shah, Karan; Cangi, Attila; Bussmann, Michael

JSON Export

{
  "updated": "2024-10-24T14:59:15.960217+00:00", 
  "conceptdoi": "10.14278/rodare.1196", 
  "created": "2021-12-09T15:27:22.833783+00:00", 
  "revision": 5, 
  "owners": [
    354
  ], 
  "links": {
    "badge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.1294.svg", 
    "doi": "https://doi.org/10.14278/rodare.1294", 
    "conceptbadge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.1196.svg", 
    "conceptdoi": "https://doi.org/10.14278/rodare.1196", 
    "bucket": "https://rodare.hzdr.de/api/files/8c34ec24-d564-46f6-8dba-0cd8e28465c1", 
    "html": "https://rodare.hzdr.de/record/1294", 
    "latest": "https://rodare.hzdr.de/api/records/1294", 
    "latest_html": "https://rodare.hzdr.de/record/1294"
  }, 
  "files": [
    {
      "bucket": "8c34ec24-d564-46f6-8dba-0cd8e28465c1", 
      "checksum": "md5:71842147eb4a673b5169967028292003", 
      "key": "dataset_scripts_deep_dive_02.zip", 
      "links": {
        "self": "https://rodare.hzdr.de/api/files/8c34ec24-d564-46f6-8dba-0cd8e28465c1/dataset_scripts_deep_dive_02.zip"
      }, 
      "size": 1399001, 
      "type": "zip"
    }
  ], 
  "doi": "10.14278/rodare.1294", 
  "metadata": {
    "resource_type": {
      "type": "dataset", 
      "title": "Dataset"
    }, 
    "language": "eng", 
    "relations": {
      "version": [
        {
          "parent": {
            "pid_value": "1196", 
            "pid_type": "recid"
          }, 
          "count": 2, 
          "last_child": {
            "pid_value": "1294", 
            "pid_type": "recid"
          }, 
          "index": 1, 
          "is_last": true
        }
      ]
    }, 
    "publication_date": "2021-10-01", 
    "doi": "10.14278/rodare.1294", 
    "license": {
      "id": "CC-BY-4.0"
    }, 
    "communities": [
      {
        "id": "rodare"
      }
    ], 
    "access_right": "open", 
    "doc_id": "1", 
    "related_identifiers": [
      {
        "identifier": "https://www.hzdr.de/publications/Publ-33194", 
        "relation": "isIdenticalTo", 
        "scheme": "url"
      }, 
      {
        "identifier": "https://www.hzdr.de/publications/Publ-39797", 
        "relation": "isReferencedBy", 
        "scheme": "url"
      }, 
      {
        "identifier": "https://www.hzdr.de/publications/Publ-33571", 
        "relation": "isReferencedBy", 
        "scheme": "url"
      }, 
      {
        "identifier": "10.14278/rodare.1196", 
        "relation": "isVersionOf", 
        "scheme": "doi"
      }
    ], 
    "pub_id": "33194", 
    "access_right_category": "success", 
    "description": "<p>This dataset contains additional data for the publication &quot;A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry&quot;. Its goal is to enable interested people to reproduce the citation analysis carried out in the aforementioned publication. &nbsp;</p>\n\n\n\n<p><strong>Prerequesites</strong></p>\n\n<p>The following software versions were used for the python version of this dataset:</p>\n\n<p>Python: 3.8.6</p>\n\n<p>Scholarly: 1.2.0</p>\n\n<p>Pyzotero: 1.4.24</p>\n\n<p>Numpy: 1.20.1</p>\n\n<p>Fitz: 1.19.1</p>\n\n<p><strong>Contents</strong></p>\n\n<p>results/ : Contains the .csv files that were the results of the citation analysis.&nbsp; Paper groupings follow the ones outlined in the publication.</p>\n\n<p>scripts/ : Contains scripts to perform the citation analysis.</p>\n\n<p>Zotero.cached.pkl : Contains the cached Zotero library.</p>\n\n\n\n<p><strong>Usage</strong></p>\n\n<p>In order to reproduce the results of the citation analysis, you can use citation_analysis.py in conjunction with cached Zotero library. Manual additions can be verified using the check_consistency script.<br>\nPlease note that you will need a Tor key for the citation analysis, and access to our Zotero library if you don&#39;t want to use the cached version. If you need this access, simply contact us.</p>", 
    "keywords": [], 
    "title": "Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry", 
    "version": "v1.1.0", 
    "creators": [
      {
        "orcid": "0000-0002-8311-0613", 
        "affiliation": "HZDR / CASUS", 
        "name": "Fiedler, Lenz"
      }, 
      {
        "orcid": "0000-0002-5480-2880", 
        "affiliation": "HZDR / CASUS", 
        "name": "Shah, Karan"
      }, 
      {
        "orcid": "0000-0001-9162-262X", 
        "affiliation": "HZDR / CASUS", 
        "name": "Cangi, Attila"
      }, 
      {
        "orcid": "0000-0002-8258-3881", 
        "affiliation": "HZDR / CASUS", 
        "name": "Bussmann, Michael"
      }
    ]
  }, 
  "conceptrecid": "1196", 
  "id": 1294, 
  "stats": {
    "volume": 310578222.0, 
    "unique_downloads": 32.0, 
    "version_unique_downloads": 92.0, 
    "unique_views": 320.0, 
    "downloads": 222.0, 
    "version_unique_views": 641.0, 
    "version_views": 1383.0, 
    "version_downloads": 493.0, 
    "version_volume": 607154931.0, 
    "views": 643.0
  }
}