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. This software package the spark scripts to generate DOIBoost, 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.

DOIBoost software toolkit 1.0

La Bruzzo S
2018

Abstract

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. This software package the spark scripts to generate DOIBoost, 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.
2018
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Python
Spark
Dataset CrossRef
Unpaywall
ORCID
Microsoft Academic Graph
Enrichment
Metadata
Aggregation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/373628
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