Pilot projects 2

The Incubator continues to provide impetus for strengthening information and data-based research at the Association.

For instance, the Incubator catalyzes the development of pioneering projects that cross the traditional boundaries between disciplines and research fields. Having initiated five innovative pilot projects in 2017, Helmholtz is strengthening the topic of Information & Data Science in a second call for applications for pilot projects and investing an additional 40 million euros in total in the future of the research.

To the press release

The Incubator continues to provide impetus for strengthening information and data-based research at the Association.

Climate change is particularly affecting the polar and permafrost regions through rising temperatures. Melting of ice sheets and thawing of permafrost are immediate consequences, leading to, among other things, a rise in sea level. These developments pose societal challenges that need to be quantified and understood. The Artificial Intelligence for Cold Regions (AI-CORE) project is a collaborative approach to unlock Artificial Intelligence (AI) methods for cryospheric research. The German Aerospace Center (DLR) will develop these together with the Alfred Wegener Institute (AWI) and the TU Dresden and make them available to the Helmholtz community as part of a platform.

Further Information and contact: Dr. Andreas Dietz (DLR)
How will the climate develop, how secure is our energy supply, and what chances does molecular medicine offer?

The rapidly increasing amount of data offers radically new opportunities to address today’s most pressing questions of society, science, and economy: Data, outcomes and predictions are, however, subject to uncertainties. The goal of the project Uncertainty Quantification is to understand these uncertainties through methods of probability theory, and to include them into research and outreach. The project connects applied researchers from the four research fields Earth & Environment, Energy, Health, and Information among each other and with Helmholtz data science experts, as well as external university partners from mathematics and econometrics.

Further Information and contact: Prof. Dr. Martin Frank (KIT) and Prof. Dr. Christiane Fuchs (HMGU)
The Pilotlab Exascale Earth System Modeling explores specific concepts for earth system models on exascale supercomputers.

So-called extreme events such as hurricanes, droughts or heavy rain triggered by climate change can lead to drastic changes in society and the environment. However, current climate models are not yet precise enough, especially when it comes to simulating such events, and they need to be much more finely resolved. However, the computing power of current supercomputers cannot simply be increased; among other things, this would require far too much energy. Therefore, fundamentally new modeling concepts are needed. In PL-EESM, scientists and computer scientists are working together to develop the necessary software and new hardware concepts.

Further Information and contact: PD Dr. Martin Schultz (Forschungszentrum Jülich)
Ptychography is a computational method to use correlated measurements in order to reconstruct an object from diffraction images.

Using such a ‘virtual lense’ allows to push microscopic imaging beyond the boundaries of classical optics.

The method recently gained much interest because of the availability of an iterative algorithm to solve the reconstruction problem and sufficient computing capacity to deal with large data sets and high computational demands.

The project embraces the challenge to push ptychography towards routine operation with various radiation sources (X-ray, electrons, XUV light). Towards this aim, optical expertise will be combined with data sciences. Hereby, Ptychography 4.0 follows the Industry 4.0 paradigm in separating data acquisition from processing such that resources will be used most efficiently.

Further Information and contact: PD Dr. Wolfgang zu Castell (HMGU) und Prof. Dr. Christian Schroer (DESY)
Satellite technology and in particular GPS- or GNSS-based systems are becoming vital for our society.

Plasma density structures in the near-Earth space can significantly influence the propagation of GPS signals and hence influence the accuracy of GPS navigation. Moreover, space plasmas can also damage satellites. To carefully evaluate these effects of the space environment, it is important to develop an accurate model of the plasma density based on a variety of direct and indirect measurements.
In this initial project we will demonstrate how machine learning tools can be used to produce a real-time global empirical model of the near-Earth plasma density based on a variety of measurements. The model that will be developed as a follow-up to this current project will then utilize all available data and will be used by a broad range of stakeholders for GPS navigation and satellite operations.

Further Information and contact: Prof. Dr. Yuri Shprits (GFZ) und Dr. Dominika Sörgel (GFZ)
To solve future grand challenges, data, computational power and analytics expertise need to be brought together at unprecedented scales.

Common computing systems exhibit a strong tendency towards centralized structures with disadvantages from a technical, legal, political and ethical perspective, especially regarding security or trust requirements. As an alternative, this interdisciplinary project facilitates the implementation of decentralized, cooperative data analytics architectures by bringing the algorithms to the data in a trustworthy and regulatory compliant way. TFDA addresses the technical, methodical and legal aspects by ensuring trustworthiness of analysis and transparency regarding the analysis in- and outputs. The project validates the results in a federated radiation therapy study and then disseminates the results more broadly.

Further information:https://tfda.hmsp.center

Contact: Mario Fritz und Ralf Floca