A recent study promoted by The Royal Society analysed the changing patterns of science and scientific collaborations and confirmed that science is increasingly global, multipolar, and networked. This trend is captured by the VVV paradigm, that is, data growth in Volume, Variety, and collection, processing and consumption Velocity. The requirements of this new science outgrow the capacity of traditional approaches. In particular: - Global, multipolar and networked scientific collaborations require dynamic computational environments capable of dealing with the VVV paradigm. - Heterogeneity of the data types and data sources to be integrated requires computational environments capable of federating a number of different technologies. - Innovative solutions for massive data storage, curation, management, and analysis require elastic access and usage of computational resources. The Hybrid Data Infrastructure (HDI) is an emerging paradigm, which assumes that different technologies, including cloud computing can be integrated to provide elastic access and usage of data and data-management capabilities needed to address the challenges of new science. The iMarine and EUBrazilOpenBio projects are underpinned by Hybrid Data Infrastructures. These infrastructures support world-wide collaboration between distributed biodiversity communities by federating heterogeneous data sources, offering innovative solutions to scientists. This is achieved by integrating advanced technologies for the management of data and by providing access to heterogeneous cloud computing resources by embedding the VENUS-C technology.

Powering Science by embedding Cloud Computing in Hybrid Data Infrastructures.

Pagano P
2012

Abstract

A recent study promoted by The Royal Society analysed the changing patterns of science and scientific collaborations and confirmed that science is increasingly global, multipolar, and networked. This trend is captured by the VVV paradigm, that is, data growth in Volume, Variety, and collection, processing and consumption Velocity. The requirements of this new science outgrow the capacity of traditional approaches. In particular: - Global, multipolar and networked scientific collaborations require dynamic computational environments capable of dealing with the VVV paradigm. - Heterogeneity of the data types and data sources to be integrated requires computational environments capable of federating a number of different technologies. - Innovative solutions for massive data storage, curation, management, and analysis require elastic access and usage of computational resources. The Hybrid Data Infrastructure (HDI) is an emerging paradigm, which assumes that different technologies, including cloud computing can be integrated to provide elastic access and usage of data and data-management capabilities needed to address the challenges of new science. The iMarine and EUBrazilOpenBio projects are underpinned by Hybrid Data Infrastructures. These infrastructures support world-wide collaboration between distributed biodiversity communities by federating heterogeneous data sources, offering innovative solutions to scientists. This is achieved by integrating advanced technologies for the management of data and by providing access to heterogeneous cloud computing resources by embedding the VENUS-C technology.
2012
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Hybrid Data Infrastructures
iMarine Project
EUBrazilOpenBio
Data Interroperability
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/6001
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