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Preprint Open Access

A Web service for executable research compendia enables reproducible publications and transparent reviews in geospatial sciences

Nüst, Daniel

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  <identifier identifierType="DOI">10.5281/zenodo.4818120</identifier>
      <creatorName>Nüst, Daniel</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-0024-5046</nameIdentifier>
      <affiliation>Institute for Geoinformatics, University of Münster, Münster, Germany</affiliation>
    <title>A Web service for executable research compendia enables reproducible publications and transparent reviews in geospatial sciences</title>
    <subject>reproducible research</subject>
    <subject>scholarly communication</subject>
    <subject>executable research compendium</subject>
    <date dateType="Issued">2021-07-08</date>
  <resourceType resourceTypeGeneral="Preprint"/>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4818119</relatedIdentifier>
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    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;The Executable Research Compendium (ERC) is a concept for packaging data, code, text, and user interface configurations in a single package to increase transparency, reproducibility, and reusability of computational research. This article introduces the ERC reproducibility service (ERS) for a publication workflow enhanced by ERCs. The ERS connects with existing scientific infrastructures and was deployed and tested with a focus on data and visualisation methods for open geospatial sciences. We describe the architecture of a reference implementation for the reproducibility service, including the created Web API. We critically discuss both the project set-up and features of ERC and ERS, and examine them in the light of various classifications for reproducible research. The ERC and ERS are found to be a powerful tool to improve reproducibility and thereby enable better investigating and understanding of computational workflows during peer review. We derive lessons learned and challenges for future scholarly publishing of computer-based geospatial research.&lt;/p&gt;</description>
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