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 CloudFAIR, 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.
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Acknowledgments
This work was supported by the São Paulo Research Foundation (FAPESP), the Brazilian Federal Research Agency CNPq, and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Finance Code 001. J. P. C. Castro was supported by UFMG (PRODIS) and C. D. Aguiar by FAPESP grant #2018/22277-8. A. C. Carniel was supported by Google as a recipient of the 2022 Google Research Scholar.
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Castro, J.P.C., Romero, L.M.F., Carniel, A.C., Aguiar, C.D. (2022). Open Science in the Cloud: The CloudFAIR Architecture for FAIR-compliant Repositories. In: Chiusano, S., et al. New Trends in Database and Information Systems. ADBIS 2022. Communications in Computer and Information Science, vol 1652. Springer, Cham. https://doi.org/10.1007/978-3-031-15743-1_6
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DOI: https://doi.org/10.1007/978-3-031-15743-1_6
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