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IE3.2/NP4.3 Media

Big data and machine learning in geosciences (co-organized)
Convener: Mikhail Kanevski  | Co-Conveners: Reik Donner , Rosa Lasaponara , Sandro Fiore , Peter Baumann , Kwo-Sen Kuo , Karsten Steinhaeuser , Nicolas Younan , Morris Riedel , Nicolas Brodu , Philip Brown 
Orals
 / Wed, 26 Apr, 08:30–12:00 / Room L2
Posters
 / Attendance Wed, 26 Apr, 17:30–19:00 / Hall X4
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This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and extremely detailed modeling efforts across various fields of geosciences.

Topics of this session will include the identification and handling of specific problems arising from the need to analyze such large-scale data sets, together with and methodological approaches towards automatically inferring relevant patterns in time and space aided by computer science-inspired techniques. Among others, this session shall address approaches from the following fields:

* Dimensionality and complexity of big data sets
* Data mining and machine learning
* Visualization and visual analytics of big data
* Complex networks and graph analysis
* Informatics and data science