From Data to Reliable Knowledge

From Data to Reliable Knowledge

Improve the standards of UQ within the Helmholtz Association – from data to reliable knowledge.

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Uncertainty quantification

Helmholtz UQ tackles uncertainty in data, analyses, and predictions from diverse domains that are represented by our use cases. We explore commonalities in estimating and dealing with uncertainty in these areas and learn from potential differences.

The UQ cycle

The UQ cycle

The central theme of this project is the UQ cycle, which combines sources of uncertainty with methods. Having a model is as valuable as our understanding of its uncertainty. Data, on the other hand, comes riddled with noise. The UQ cycle comprises identification, presentation, analysis, and modeling of the sources of uncertainty.

Why UQ in Helmholtz? Why now?

Why UQ in Helmholtz? Why now?

  • Many innovative modeling and computational efforts in Helmholtz need to be combined with a myriad of complex data.
  • Recent advances in mathematical methods have not yet been fully exploited in Helmholtz applications.
  • Helmholtz UQ complements other Helmholtz platforms (HAICU, HDF, HIDA, HIDSS) and pilot projects (HAF, RedMod, Sparse2Big).
  • Helmholtz UQ is a cross-disciplinary collaboration focused on quantifications of uncertainty, which is ubiquitous across research fields and other Helmholtz projects.

Latest Posts

News and Events.

New UQ Professor at KIT

New UQ Professor at KIT

Prof. Dr. Sebastian Krumscheid has taken up a position as professor for uncertainty quantification at KIT.

UQ Spring Meeting in Hamburg

UQ Spring Meeting in Hamburg

The first UQ project meeting of the year took place between the 16th and the 20th of May. It also included a PhD Sprint!

Presentation at OSM 2022

Presentation at OSM 2022

Nabir Mamnun, a PhD student at AWI presented his work at the OSM Meeting 2022 with a talk titled “Uncertainty in ocean biogeochemical simulation: application of ensemble data assimilation to a one-dimensional model”.