Helmholtz to invest in innovative information and data science research projects
Big data and artificial intelligence offer enormous potential for every area of relevance to our society, including research into climate change, the Earth system, and health. As an important player in the field of information and data science, Helmholtz is now funding a second round of pioneering research projects with about 20 million euros.
Following a successful first round of calls for applications in 2017— in the course of which 17 million euros of grants were awarded – additional projects run by the Helmholtz Information and Data Science Incubator are now set to receive funding as well. The projects will receive a total of 20 million euros in funding for a period of three years. Four strategically relevant research projects underpinned by excellent scientific work were immediately selected. A further promising research approach is still undergoing revisions, and three additional projects are slated to receive start-up funding. These pioneering research projects were selected following a peer review process supported by an international panel of renowned experts.
“We are making great efforts in the Association to create new knowledge from the enormous data sets produced in all research areas. The selection of these new projects led by top-flight researchers demonstrates Helmholtz’ incredibly strong performance. With projects like these we rapidly bring our digitalization strategy to life,” says Otmar D. Wiestler, President of Helmholtz. “We use information and data sciences, for instance to simulate extreme weather events, improve Earth monitoring systems, and fundamentally enhance microscopy technology,” Wiestler continues.
The four research projects that were immediately selected are:
Artificial Intelligence for Cold Regions (AI-CORE)
Climate Change is affecting the polar and permafrost regions particularly due to rising temperatures. The melting of ice shields and the thawing of permafrost are immediate results, leading among other things to global sea level rise. These developments pose a considerable challenge to society and need to be thoroughly understood and quantified. In the context of “Artificial Intelligence for Cold Regions” (AI-CORE), we will follow a joint approach to make methods of Artificial Intelligence (AI) accessible to cryosphere research. The German Aerospace Center (DLR) will develop these methods together with the Alfred Wegener Institute (AWI) and the TU Dresden and make them available to the Helmholtz Association within the framework of a common platform.
Further Information and contact: Dr. Andreas Dietz (DLR), Andreas.Dietz@dlr.de
Uncertainty Quantification – From Data to Reliable Knowledge (UQ)
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.
Pilot Lab Exascale Earth System Modelling (PL-EESM)
Pilot Lab Exascale Earth System Modelling researches specific concepts for Earth system models on exascale supercomputers. So-called extreme events – such as hurricanes caused by climate change as well as droughts or torrential rains – can lead to dramatic changes in our society and the environment. At the same time, current climate models aren’t precise enough to simulate these exact types of events and need to be made capable of working at a much higher resolution. But the computing power of today’s supercomputers cannot simply be increased – among other things, this would consume far too much energy. This means that completely new types of modeling concepts will be required. Researchers and IT experts are working together at PL-EESM to develop the necessary software and new hardware concepts.
Further Information and contact: PD Dr. Martin Schultz (FZ Jülich), firstname.lastname@example.org
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.
Helmholtz Information and Data Science Incubator
The provision of funding to these projects is one of the activities of the Helmholtz Information and Data Science Incubator. Together with five newly founded, Helmholtz-wide high-tech platforms, the Incubator is part of the Helmholtz Information & Data Science Framework. Helmholtz will be investing a total of 50 million euros in the framework each year on a continual basis.
The new platforms include the Helmholtz Artificial Intelligence Cooperation Unit (HAICU) and Helmholtz Information & Data Science Academy (HIDA), which connects the Helmholtz Information & Data Science Schools (HIDSS). These platforms are joined by the Helmholtz Federated IT Services (HIFIS), the Helmholtz Imaging Platform (HIP), and the Helmholtz Metadata Collaboration Platform (HMC).
As a long-term, bottom-up process spanning the entirety of Helmholtz, the framework was initiated in 2016 and has been pooling the Helmholtz Association’s diverse expertise in the field of information and data science since then. The Incubator establishes the concrete terms of the Helmholtz digitalization strategy, brings creative minds from every area of Helmholtz into contact with one another on a regular basis, lays the foundation for innovative, interdisciplinary networks, and identifies the topic areas and technologies of the future.
Helmholtz contributes to solving major challenges facing society, science, and the economy through top-level scientific achievements in six Research Fields: Energy, Earth and Environment, Health, Key Technologies, Matter, and Aeronautics, Space, and Transport. With more than 40,000 employees at 19 Research Centers and an annual budget of around 4.7 billion euros, Helmholtz is the largest scientific organization in Germany. Its work is rooted in the tradition of the great natural scientist Hermann von Helmholtz (1821–1894).