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Recolector de Ciencia Abierta, RECOLECTA
Part of book or chapter of book . 2021 . Peer-reviewed
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Recolector de Ciencia Abierta, RECOLECTA
Part of book or chapter of book . 2020 . Peer-reviewed
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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Recolector de Ciencia Abierta, RECOLECTA
Part of book or chapter of book . 2021 . Peer-reviewed
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Challenge 8: Oceans of Big Data and Artificial Intelligence

Authors: Logares, Ramiro; Alós, Josep; Catalán, Ignacio Alberto; Crespo Solana, Ana; Campo, Javier del; Ercilla, Gemma; Fablet, Ronan; +21 Authors

Challenge 8: Oceans of Big Data and Artificial Intelligence

Abstract

Oceans are no longer inaccessible places for data acquisition. High-throughput technological advances applied to marine sciences (from genes to global current patterns) are generating Big Data sets at unprecedented rates. How to manage, store, analyse, useand transform this data deluge into knowledge is now a fundamental challenge for ocean sciences. Artificial Intelligence and Machine Learning are the most promising and exciting approaches addressing this challenge. These technologies are directly applicable to many data analysis problems and major challenges in the study of the ocean microbiome, ocean observation and forecasting, animal biology, ecology and conservation, resource management, and marine geosciences. We are only at the beginning of an era when machines are able to solve complex tasks that, until today, have required human expertise. We envision that the combination of ocean Big Data and Artificial Intelligence will provide the means for ground-breaking advances in our understanding of ocean functioning.

18 pages, 3 figures

Peer reviewed

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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