Publication details.


Author(s):Logares, R.; Alós, J.; Catalán, I.A.; Solana, A. C.; del Campo, J.; Ercilla, G.; Fablet, R.; Fernández-Guerra, A.; Galí, M.; Gasol, J. M.; González, A. F.; Hernández-García, E.; López, C.; Massana, R.; Fontanet, L. M.; Palmer, M.; Pascual, S.; Pascual, A.; Pérez, F.; Pintado, J.; Portabella, M.; Ramasco, J. J.; Richter, D. J.; Sallarès, V.; Sánchez, P.; Sanllehi, J.; Turiel, A.; Villaseñor, A.;
Title:Oceans of Big Data and Artificial Intelligence. Chapter 8
Book title:Ocean Science Challenges For 2030
Editor:Pascual, A. and Macias, D
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.

Related staff

  • Ananda Pascual Ascaso
  • Ignacio A. Catalán Alemany
  • Miguel Palmer Vidal
  • Josep Alós Crespí
  • Josep Alós Crespí
  • Related departments

  • Marine Ecology
  • Oceanography and Global Change
  • Related research groups

  • Marine Ecosystems Dynamics
  • Marine Technologies, Operational and Coastal Oceanography