Conference paper Open Access
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.3336609</identifier> <creators> <creator> <creatorName>Kennedy, David N</creatorName> <givenName>David N</givenName> <familyName>Kennedy</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-9377-0797</nameIdentifier> <affiliation>Eunice Kennedy Shriver Center, Department of Psychiatry University of Massachusetts Medical School Worcester, MA, United States</affiliation> </creator> </creators> <titles> <title>The ReproPub: A hybrid research object for supporting publication-level re-execution and generalization of neuroimaging research findings</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2019</publicationYear> <subjects> <subject>reproducible research, re-execution, data publication, software publication, containers</subject> </subjects> <dates> <date dateType="Issued">2019-07-15</date> </dates> <resourceType resourceTypeGeneral="Text">Conference paper</resourceType> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3336609</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3336608</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/ro</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="http://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"><p>In this report we introduce the &lsquo;ReproPub&rsquo;, a publication that includes the complete provenance of its experimental data, workflow, execution environment, and results. The ReproPub concept supports re-executability of the original finding, which, it is argued, supports a more systematic exploration of the generalizability of the finding and hence enhances the evaluation of its reproducibility.</p></description> <description descriptionType="Other">Preprint submitted to RO2019 workshop at IEEE eScience Conference 2019</description> </descriptions> </resource>
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