Articles | Volume 91
https://doi.org/10.5194/polf-91-45-2023
https://doi.org/10.5194/polf-91-45-2023
Scientific article
 | 
04 Sep 2023
Scientific article |  | 04 Sep 2023

Big data in Antarctic sciences – current status, gaps, and future perspectives

Angelika Graiff, Matthias Braun, Amelie Driemel, Jörg Ebbing, Hans-Peter Grossart, Tilmann Harder, Joseph I. Hoffman, Boris Koch, Florian Leese, Judith Piontek, Mirko Scheinert, Petra Quillfeldt, Jonas Zimmermann, and Ulf Karsten

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Cited articles

Albarano, L., Esposito, R., Ruocco, N., and Costantini, M.: Genome Mining as New Challenge in Natural Products Discovery, Mar. Drugs, 18, 199, https://doi.org/10.3390/md18040199, 2020. 
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Baumhoer, C., Andreas, D., Kneisel, C., and Kuenzer, C.: Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning, Remote Sens., 11, 1–22  https://doi.org/10.3390/rs11212529, 2019. 
Bayraktarov, E., Ehmke, G., O'Connor, J., Burns, E. L., Nguyen, H. A., McRae, L., Possingham, H. P., and Lindenmayer, D. B.: Do Big Unstructured Biodiversity Data Mean More Knowledge? Front. Ecol. Evol., 6, 239, https://doi.org/10.3389/fevo.2018.00239, 2019. 
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Short summary
There are many approaches to better understanding Antarctic processes that generate very large data sets (Antarctic big data). For these large data sets there is a pressing need for improved data acquisition, curation, integration, service, and application to support fundamental scientific research, and this article describes and evaluates the current status of big data in various Antarctic scientific disciplines, identifies current gaps, and provides solutions to fill these gaps.