Open Science in the Cloud: The CloudFAIR Architecture for FAIR-compliant Repositories

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Author(s): Show less -	Castro, Joao Pedro C. ; Romero, Lucas M. F. ; Carniel, Anderson Chaves ; Aguiar, Cristina D. ; Chiusano, S ; Cerquitelli, T ; Wrembel, R ; Norvag, K ; Catania, B ; Vargas-Solar, G ; Zumpano, E Total Authors: 11
Document type:	Journal article
Source:	NEW TRENDS IN DATABASE AND INFORMATION SYSTEMS, ADBIS 2022; v. 1652, p. 11-pg., 2022-01-01.
Abstract
Fulfilling the FAIR Principles is a challenge that requires the management of research data and metadata considering the inherent big data complexity of volume, variety, and velocity. A suitable solution to deal with this problem is to combine a software reference architecture with a cloud computing environment. In this paper, we propose Cloud-FAIR, a novel Open Science architecture with an infrastructure located entirely in the cloud, which unburdens scientists in data and metadata management and improves performance. CloudFAIR also addresses security issues related to data encryption. We conducted performance tests with a real-world dataset to assess the efficiency of CloudFAIR. Compared to BigFAIR, the proposed architecture provided performance gains that ranged from 41.03% up to 75.95% when the issued queries required the retrieval of both data and metadata. (AU)

FAPESP's process:	18/22277-8 - Processing of OLAP and SOLAP Queries on Parallel and Distributed Environments
Grantee:	Cristina Dutra de Aguiar
Support Opportunities:	Regular Research Grants