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

• Published in: Polarforschung
• Main Authors: Graiff, Angelika, Braun, Matthias, Driemel, Amelie, Ebbing, Jörg, Grossart, Hans-Peter, Harder, Tilmann, Hoffman, Joseph I., Koch, Boris, Leese, Florian, Piontek, Judith, Scheinert, Mirko, Quillfeldt, Petra, Zimmermann, Jonas, Karsten, Ulf
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2023
• Subjects: article; Verlagsveröffentlichung; Arctic; Antarctic; Southern Ocean; Antarc*; Antarctica; Polarforschung
• Online Access: https://doi.org/10.5194/polf-91-45-2023; https://noa.gwlb.de/receive/cop_mods_00068638; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00067057/polf-91-45-2023.pdf; https://polf.copernicus.org/articles/91/45/2023/polf-91-45-2023.pdf

This paper was initiated by a multidisciplinary Topic Workshop in the frame of the Deutsche Forschungsgemeinschaft Priority Program 1158 “Antarctic Research with Comparative Investigations in Arctic Ice Areas”, and hence it represents only the national view without claiming to be complete but is intended to provide awareness and suggestions for the current discussion on so-called big data in many scientific fields. The importance of the polar regions and their essential role for the Earth system are both undoubtedly recognized. However, dramatic changes in the climate and environment have been observed first in the Arctic and later in Antarctica over the past few decades. While important data have been collected and observation networks have been built in Antarctica and the Southern Ocean, this is a relatively data-scarce region due to the challenges of remote data acquisition, expensive labor, and harsh environmental conditions. There are many approaches crossing multiple scientific disciplines to better understand Antarctic processes; to evaluate ongoing climatic and environmental changes and their manifold ecological, physical, chemical, and geological consequences; and to make (improved) predictions. Together, these approaches generate very large, multivariate data sets, which can be broadly classified as “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. Based on deficiencies in crossing disciplines and to attract further interest in big data in Antarctic sciences, this article will (i) describe and evaluate the current status of big data in various Antarctic-related scientific disciplines, (ii) identify current gaps, (iii) and provide solutions to fill these gaps.