
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>This report compares and analyses the level of FAIRness of the datasets uploaded on Dataverse UNIMI and Zenodo by researchers of the University of Milan. The aim is to highlight the importance of FAIR principles in the management and sharing of research data by UNIMI's academic community, underlining how the choice of the repository significantly influences data quality, accessibility and reuse. The analysis conducted in this report is based on 885 datasets that were extracted using the public and open OpenAIRE EXPLORE infrastructure to derive the datasets published on the Dataverse UNIMI and Zenodo repositories by researchers at the University of Milan between 2019 and 2024. Metadata were extracted through the use of two original programmes - developed in Python - to assess their FAIRness and were then analysed by repository and comparatively via R. Consistently with FAIR data management, the data which the report was based on is available on Dataverse UNIMI at the DOI indicated below. --- Il presente report confronta ed analizza il livello di FAIRness dei dataset caricati su Dataverse UNIMI e Zenodo da parte di ricercatori e ricercatrici dell’Università degli Studi di Milano. L’intento è quello di evidenziare l’importanza dei principi FAIR nella gestione e condivisione dei dati della ricerca da parte della comunità scientifica d’Ateneo, sottolineando come la scelta del repository influenzi significativamente la qualità, l’accessibilità e il riutilizzo dei dati. L’analisi condotta in questo report si basa su 885 dataset che sono stati estrapolati utilizzando l'infrastruttura pubblica e aperta OpenAIRE EXPLORE per ricavare i dataset pubblicati sui repository Dataverse UNIMI e Zenodo da ricercatori e ricercatrici dell’Università degli Studi di Milano tra il 2019 e il 2024. I metadati sono stati estratti attraverso l'utilizzo di due programmi originali - sviluppati in Python - per valutarne la FAIRness e sono stati poi analizzati per repository e in modo comparato tramite R. In coerenza con una gestione dei dati FAIR, i dati alla base del report sono disponibili su Dataverse UNIMI, al DOI indicato sotto.
Research data repository, Data stewardship, FAIR principles, Research data management, Dataverse, Quality control, Zenodo
Research data repository, Data stewardship, FAIR principles, Research data management, Dataverse, Quality control, Zenodo
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
