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Dataset Open Access

DOIBoost Dataset Dump

La Bruzzo, Sandro; Manghi, Paolo; Mannocci, Andrea


MARC21 XML Export

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    <subfield code="a">&lt;p&gt;&amp;nbsp;&lt;/p&gt;

&lt;p&gt;Research in information science and scholarly communication strongly relies on the availability of openly accessible datasets of metadata and, where possible, their relative payloads. To this end, CrossRef plays a pivotal role by providing free access to its entire metadata collection, and allowing other initiatives to link and enrich its information. Therefore, a number of key pieces of information result scattered across diverse datasets and resources freely available online. As a result of this fragmentation, researchers in this domain end up struggling with daily integration problems producing a plethora of ad-hoc datasets, therefore incurring in a waste of time, resources, and infringing open science best practices.&amp;nbsp;DOIBoost is&amp;nbsp;a metadata collection that enriches CrossRef with inputs from Microsoft Academic Graph, ORCID, and Unpaywall for the purpose of supporting high-quality and robust research experiments, saving times to researchers and enabling their comparison.&lt;/p&gt;

&lt;p&gt;This entry consists of two files: &lt;strong&gt;doiBoost.tar.gz&lt;/strong&gt; (which contains a set of part.gz files, each one containing the JSON files realtive to the enriched CrossRef records) and &lt;strong&gt;termsOfUse.doc&amp;nbsp;&lt;/strong&gt;(which contains details on the terms of use of DOIBoost).&lt;/p&gt;

&lt;p&gt;Note that this records comes with two relationships to other results of this experiment:&amp;nbsp;&lt;/p&gt;

&lt;ol&gt;
	&lt;li&gt;link to the data paper: for more information on how the dataset is (and can be) generated;&lt;/li&gt;
	&lt;li&gt;link to the software: to repeat the experiment&amp;nbsp; .&lt;/li&gt;
&lt;/ol&gt;

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