October 1, 2021 Dataset Open Access

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

DataCite XML Export

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  <identifier identifierType="DOI">10.14278/rodare.1294</identifier>
  <creators>
    <creator>
      <creatorName>Fiedler, Lenz</creatorName>
      <givenName>Lenz</givenName>
      <familyName>Fiedler</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-8311-0613</nameIdentifier>
      <affiliation>HZDR / CASUS</affiliation>
    </creator>
    <creator>
      <creatorName>Shah, Karan</creatorName>
      <givenName>Karan</givenName>
      <familyName>Shah</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-5480-2880</nameIdentifier>
      <affiliation>HZDR / CASUS</affiliation>
    </creator>
    <creator>
      <creatorName>Cangi, Attila</creatorName>
      <givenName>Attila</givenName>
      <familyName>Cangi</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-9162-262X</nameIdentifier>
      <affiliation>HZDR / CASUS</affiliation>
    </creator>
    <creator>
      <creatorName>Bussmann, Michael</creatorName>
      <givenName>Michael</givenName>
      <familyName>Bussmann</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-8258-3881</nameIdentifier>
      <affiliation>HZDR / CASUS</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-10-01</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/1294</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-33194</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-39797</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-33571</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.1196</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
  </relatedIdentifiers>
  <version>v1.1.0</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This dataset contains additional data for the publication &amp;quot;A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry&amp;quot;. Its goal is to enable interested people to reproduce the citation analysis carried out in the aforementioned publication. &amp;nbsp;&lt;/p&gt;



&lt;p&gt;&lt;strong&gt;Prerequesites&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;The following software versions were used for the python version of this dataset:&lt;/p&gt;

&lt;p&gt;Python: 3.8.6&lt;/p&gt;

&lt;p&gt;Scholarly: 1.2.0&lt;/p&gt;

&lt;p&gt;Pyzotero: 1.4.24&lt;/p&gt;

&lt;p&gt;Numpy: 1.20.1&lt;/p&gt;

&lt;p&gt;Fitz: 1.19.1&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Contents&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;results/ : Contains the .csv files that were the results of the citation analysis.&amp;nbsp; Paper groupings follow the ones outlined in the publication.&lt;/p&gt;

&lt;p&gt;scripts/ : Contains scripts to perform the citation analysis.&lt;/p&gt;

&lt;p&gt;Zotero.cached.pkl : Contains the cached Zotero library.&lt;/p&gt;



&lt;p&gt;&lt;strong&gt;Usage&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;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.&lt;br&gt;
Please note that you will need a Tor key for the citation analysis, and access to our Zotero library if you don&amp;#39;t want to use the cached version. If you need this access, simply contact us.&lt;/p&gt;</description>
  </descriptions>
</resource>