FAIREST Metrics and Assessment Data

d’Aquin, Mathieu; Kirstein, Fabian; Schimmler, Sonja; Oliveira, Daniela; Urbanek, Sebastian

FAIREST Metrics and Assessment Data

dc.contributor.author	d’Aquin, Mathieu
dc.contributor.author	Kirstein, Fabian
dc.contributor.author	Schimmler, Sonja
dc.contributor.author	Oliveira, Daniela
dc.contributor.author	Urbanek, Sebastian
dc.date.accessioned	2023-10-11T17:28:54Z
dc.date.available	2023-10-11T17:28:54Z
dc.date.issued	2021-11-08
dc.description.abstract	<p>This data supplements the article “FAIREST: A Framework for Assessing Research Repositories”. In the article, we introduce the FAIREST principles, an extension of the well-known FAIR principles. Along these principles, we provide comprehensive metrics for assessing and selecting solutions for building digital repositories for research artefacts. The metrics are based on two pillars:</p> <ol> <li>an analysis of established features and functionalities, drawn from existing solutions, </li> <li>a literature review on general requirements for digital repositories for research artefacts and related systems.</li> <ol> <br /> <p>We further describe an assessment of 11 widespread solutions, with the goal to provide an overview of the current landscape of research data repository solutions, identifying gaps and research challenges to be addressed. The solutions are:</p> <ul> <li>– ResearchGate</li> <li>– Academia.edu</li> <li>– Zenodo</li> <li>– arXiv</li> <li>– Bibsonomy</li> <li>– Figshare</li> <li>– CKAN</li> <li>– DSpace</li> <li>– Invenio</li> <li>– Dataverse</li> <li>– EPrints</li> <ul> <br /> <h5>Overview of the data</h5> <p><b>01 FAIREST Assessment Metrics and Solutions (All-in-one).xlsx</b></p> <p>This Excel file includes both the assessment metrics and the results for the 11 solutions</p> <br /> <p><b>02 FAIREST Assessment Metrics.csv</b></p> <p>The assessment metrics as CSV</p> <br /> <p><b>XX FAIREST Assessment XXX.csv</b></p> <p>Assessment result for the respective solution</p> <br /> <p><b>14 FAIREST Assessment Template.xlsx</b></p> <p>A template to apply the metrics to an individual solution</p> <p>Note: Fill in your assessment in column F and get the result at the bottom of the sheet</p>	en
dc.description.sponsorship	This research was supported by the Fundação para a Ciência e a Tecnologia through the LASIGE Research Unit, UIDB/00408/2020 and UIDP/00408/2020. This work was supported by the Federal Ministry of Education and Research of Germany (BMBF) under grant no. 16DII12 ("Deutsches Internet-Institut").
dc.identifier.citation	Mathieu d'Aquin, Fabian Kirsten, Daniela Oliveira, Sonja Schimmler, & Sebastian Urbanek. (2021). FAIREST Metrics and Assessment Data (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5282929
dc.identifier.doi	10.5281/zenodo.5282929
dc.identifier.uri	https://zenodo.org/record/5282929
dc.identifier.uri	https://beta.weizenbaum-library.de/handle/id/382
dc.language.iso	eng
dc.publisher	zenodo
dc.relation.issupplementto	https://doi.org/10.1162/dint_a_00159
dc.relation.issupplementto	https://www.weizenbaum-library.de/handle/id/365
dc.rights	open access
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Research Repositories
dc.subject	FAIR Principles
dc.subject	Open Access
dc.subject	Research Data
dc.subject.ddc	004 Informatik
dc.title	FAIREST Metrics and Assessment Data
dc.type	ResearchData
dc.type.status	publishedVersion
dcmi.type	Dataset
local.researchgroup	Digitalisierung der Wissenschaft
local.researchtopic	Mensch – Arbeit – Wissen