Thesis Open Access

Enabling the data FAIRness of version control systems

Fahrenfort, Cas

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  <identifier identifierType="DOI">10.5281/zenodo.3583010</identifier>
      <creatorName>Fahrenfort, Cas</creatorName>
      <affiliation>University of Amsterdam</affiliation>
    <title>Enabling the data FAIRness of version control systems</title>
    <contributor contributorType="Supervisor">
      <contributorName>Zhao, Zhiming</contributorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-6717-9418</nameIdentifier>
      <affiliation>University of Amsterdam</affiliation>
    <contributor contributorType="Supervisor">
      <contributorName>Gillebaart, Thijs</contributorName>
    <date dateType="Issued">2019-12-18</date>
  <resourceType resourceTypeGeneral="Text">Thesis</resourceType>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3583009</relatedIdentifier>
    <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;&amp;nbsp;Many kinds of different scientific data are being produced every day by research institutes across the&lt;/p&gt;

&lt;p&gt;globe. Scientists are interested in using this data, but often have difficulties when trying to obtain&lt;/p&gt;

&lt;p&gt;access to data that has been created and is stored by external organizations, due to incompatible data&lt;/p&gt;

&lt;p&gt;management standards. The Findability, Accessibility, Interoperability, Re-usability (FAIR) principles&lt;/p&gt;

&lt;p&gt;are guiding principles for scientific data management and stewardship, which have been developed to&lt;/p&gt;

&lt;p&gt;facilitate knowledge discovery by introducing common standards for human and machine interaction with&lt;/p&gt;

&lt;p&gt;data, utilizing Persistent Identifiers (PIDs) and metadata. Several technologies and services have been&lt;/p&gt;

&lt;p&gt;introduced which leverage these principles. However, all aforementioned standards, technologies, and&lt;/p&gt;

&lt;p&gt;services are intended for static data and do not provide adequate support for dynamic and evolutionary&lt;/p&gt;

&lt;p&gt;data, e.g. software source code, which is often managed by Version Control Systems (VCSs) such as Git&lt;/p&gt;

&lt;p&gt;and Subversion. This research investigated the current approaches to managing persistently identified&lt;/p&gt;

&lt;p&gt;data through VCSs and found them to be lacking in diversity of supported VCSs and persistent publishing&lt;/p&gt;

&lt;p&gt;systems, and proposed a novel system which allows for direct publishing of repositories from multiple&lt;/p&gt;

&lt;p&gt;VCSs to multiple, external publishing systems through a web-accessed interface. This initial idea has&lt;/p&gt;

&lt;p&gt;also been published as a poster in the 2019 eScience Proceedings [1], which originated from an industry&lt;/p&gt;

&lt;p&gt;problem posed by Grasple [2]. Additionally, at the end of the thesis, several assertions and conclusions&lt;/p&gt;

&lt;p&gt;about the state of the art of persistent publishing of evolutionary data, most notably software source&lt;/p&gt;

&lt;p&gt;code, are made which detail important problems that need additional solutions.&lt;/p&gt;</description>
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