NP4.3

This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and 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 methodological approaches towards semi or fully automated inference of 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 in Earth sciences
• Machine learning, including deep learning and other advanced approaches
• Visualization and visual analytics of big data
• Informatics and data science
• Emerging big data paradigms, such as datacubes

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Co-organized as AS5.20/CL5.25/ESSI2.3/GD8.5/HS3.5/NH11.11/SM7.8
Convener: Mikhail Kanevski  | Co-conveners: Peter Baumann , Sandro Fiore , Kwo-Sen Kuo , Nicolas Younan 
Orals
| Mon, 08 Apr, 10:45–12:30, 14:00–18:00
 
Room L3
Posters
| Attendance Tue, 09 Apr, 10:45–12:30
 
Hall X4
This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and 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 methodological approaches towards semi or fully automated inference of 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 in Earth sciences
• Machine learning, including deep learning and other advanced approaches
• Visualization and visual analytics of big data
• Informatics and data science
• Emerging big data paradigms, such as datacubes