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Virtual earth cloud: a multi-cloud framework for enabling geosciences digital ecosystems

Academic Article
Publication Date:
2023
abstract:
Humankind is facing unprecedented global environmental and social challenges in terms of food, water and energy security, resilience to natural hazards, etc. To address these challenges, international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan. The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions (providing the best available knowledge) and avoid potentially negative impacts on society and the environment. Such knowledge platforms must build on the recent and next coming digital technologies that have transformed society - including the science and engineering sectors. Big Earth Data (BED) science aims to provide the methodologies and instruments to generate knowledge from numerous, complex, and diverse data sources. BED science requires the development of Geoscience Digital Ecosystems (GEDs), which bank on the combined use of fundamental technology units (i.e. big data, learning-driven artificial intelligence, and network-based computing platform) to enable the development of more detailed knowledge to observe and test planet Earth as a whole. This manuscript contributes to the BED science research domain, by presenting the Virtual Earth Cloud: a multi-cloud framework to support GDE implementation and generate knowledge on environmental and social sustainability.
Iris type:
01.01 Articolo in rivista
Keywords:
Earth observation; geosciences digital ecosystem; virtual cloud; big earth data; multi-cloud; interoperability science
List of contributors:
Nativi, Stefano; Mazzetti, Paolo; Santoro, Mattia
Authors of the University:
MAZZETTI PAOLO
NATIVI STEFANO
SANTORO MATTIA
Handle:
https://iris.cnr.it/handle/20.500.14243/437754
Published in:
INTERNATIONAL JOURNAL OF DIGITAL EARTH (PRINT)
Journal
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URL

https://doi.org/10.1080/17538947.2022.2162986
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