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Big Data in Marine Science
Big Data in Marine Science
This document explores the potential of big data, i.e. large volumes of high variety data collected at high velocity, to advance marine science. Marine science is rapidly entering the digital age. Expansions in the scope and scale of ocean observations, as well as automated sampling and ‘smart sensors’, are leading to a continuous flood of data. This provides opportunities to transform the way we study and understand the ocean through more complex and interdisciplinary analyses, and offers novel approaches for the management of marine resources. However, more data do not necessarily mean that we have the right data to answer many critical scientific questions and to make well-informed, data-driven management decisions on the sustainable use of ocean resources. To increase the value of the wealth of marine big data, it must be openly shared, interoperable and integrated into complex transdisciplinary analyses using artificial intelligence.
- University of East Anglia United Kingdom
- University of Copenhagen Denmark
- Universidade de Vigo Spain
- NORCE NORWEGIAN RESEARCH CENTRE AS Norway
- Institut National des Sciences de l Univers France
Artificial intelligence, Aquaculture, [SDU.STU.OC] Sciences of the Universe [physics]/Earth Sciences/Oceanography, Big data, Habitat mapping, Marine science, Machine learning, Marine protected areas, Climate change, Marine biogeochemistry, Marine biological observations
Artificial intelligence, Aquaculture, [SDU.STU.OC] Sciences of the Universe [physics]/Earth Sciences/Oceanography, Big data, Habitat mapping, Marine science, Machine learning, Marine protected areas, Climate change, Marine biogeochemistry, Marine biological observations
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citations 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).8 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.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 226 download downloads 79 - 226views79downloads
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