Metrics
125,655 Downloads
Contact Share

bonndata is the institutional, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn.
bonndata is provided by the University IT and Data Center and maintained by the Research Data Service Center.
Ready to get started with bonndata?
Have a look at our User Guide to get to know the bonndata workflow, tips and tricks!
Questions? Need assistance?
Get in touch: researchdata@uni-bonn.de
Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

411 to 420 of 3,088 Results
Amphora_37_model.zip
Oct 22, 2024 - Attic Black-Figure Amphora in the Academic Art Museum (Inv. 37)
ZIP Archive - 1.1 GB - MD5: 14c6b0f6cee3293c27be4add5b105092
Identifying spatio-temporal drivers of extreme events [data set]
Identifying spatio-temporal drivers of extreme events [data set]
Oct 21, 2024
Shams Eddin, Mohamad Hakam; Gall, Juergen, 2024, "Identifying spatio-temporal drivers of extreme events [data set]", https://doi.org/10.60507/FK2/RD9E33, bonndata, V1
This data set allows to systematically evaluate approaches for the task of identifying extreme events in water cycle components by developing deep neural networks that detect anomalies and drivers of extremes in simulated data.
AFR-11.7z
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
7Z Archive - 31.5 GB - MD5: 23895c5e11a26feb1b6fbdda4a7c0928
Data
CAS-11.7z
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
7Z Archive - 30.4 GB - MD5: 22342067b8c7d1830ebeee710e069e92
Data
CERRA.7z.001
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
Unknown - 100.0 GB - MD5: 38eaa7688d119a470089a197990a5d24
Data
CERRA.7z.002
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
Unknown - 95.8 GB - MD5: 15720a1f0be84ab32c7e058b9c9ac7b9
Data
EAS-11.7z
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
7Z Archive - 29.8 GB - MD5: 4f385d00203e698de00d46750c3b2f56
Data
EUR-11.7z
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
7Z Archive - 11.9 GB - MD5: 644bbc9d564a934211caa7331f6cac29
Data
NAM-11.7z
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
7Z Archive - 20.6 GB - MD5: 516c8be75ebf70693b2f81b06e0ac0ab
Data
NOAA_CERRA.7z
Oct 21, 2024 - Identifying spatio-temporal drivers of extreme events [data set]
7Z Archive - 39.8 GB - MD5: ad2c687c8e6d00a58b80b12703f46bd8
Data
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.