Projects

SCC is involved in various research projects. Research focuses on computational science & engineering, data science and secure IT federations as well as dynamic and distributed IT infrastructures. Universities and research institutions as well as companies, national and international, are among the cooperation partners of the SCC.

Smart weather predictions for the 21st century through probabilistic AI-models initialized with strom-resolving climate projections
Smart weather predictions for the 21st century through probabilistic AI-models initialized with strom-resolving climate projections

The ongoing warming of the earth's climate due to man-made climate change is fundamentally changing our weather. Traditionally, weather forecasts have been made based on numerical models, so-called Numerical Weather Predictions (NWP). Data-driven machine learning models and in particular deep neural networks offer the potential as surrogate models for fast and (energy) efficient emulation of NWP models. As part of the SmartWeather21 project, we want to investigate which DL architecture for NWP is best suited for weather forecasting in a warmer climate, based on the high-resolution climate projections generated with ICON as part of WarmWorld. To incorporate the high resolutions of the WarmWorld climate projections, we will develop data- and model-parallel approaches and architectures for weather forecasting in a warmer climate. Furthermore, we will investigate which (learnable combinations of) variables from the ICON climate projections provide the best, physically plausible forecast accuracy for weather prediction in a warmer climate. With this in mind, we develop dimension reduction techniques for the various input variables that learn a latent, lower-dimensional representation based on the accuracy of the downstream weather forecast as an upstream task. The increased spatial resolution of the ICON simulations also allows conclusions to be drawn about the uncertainties of individual input and output variables at lower resolutions. As part of SmartWeather21, we will develop methods that parameterise these uncertainties using probability distributions and use them as input variables with lower spatial resolution in DL-based weather models. These can be propagated through the model as part of probabilistic forecasts.

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EOSC Beyondpixabay.com
EOSC Beyond

EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers

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Holistic Imaging and Molecular Analysis in life-threatening Ailmentsunsplash.com alvaro-reyes
Holistic Imaging and Molecular Analysis in life-threatening Ailments

The overall goal of this project is to improve the radiological diagnosis of human prostate cancer in clinical MRI by AI-based exploitation of information from higher resolution modalities. We will use the brilliance of HiP-CT imaging at beamline 18 and an extended histopathology of the entire prostate to optimise the interpretation of MRI images in the context of a research prototype. In parallel, the correlation of the image data with the molecular properties of the tumours is planned for a better understanding of invasive tumour structures. An interactive multi-scale visualisation across all modalities forms the basis for vividly conveying the immense amounts of data. As a result, at the end of the three-year project phase, the conventional radiological application of magnetic resonance imaging (MRI) is to be transferred into a diagnostic standard that also reliably recognises patients with invasive prostate tumours that have often been incorrectly diagnosed to date, taking into account innovative AI algorithms. In the medium term, a substantial improvement in the care of patients with advanced prostate carcinoma can therefore be expected. In addition, we will make the unique multimodal data set created in the project, including visualisation tools, available as open data to enable further studies to better understand prostate cancer, which could potentially lead to novel diagnostic and therapeutic approaches.

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Ongoing Projects

Smart weather predictions for the 21st century through probabilistic AI-models initialized with strom-resolving climate projections - SmartWeather21

Contact: Dr. Charlotte Debus
Funding: BMBF
since 2024-05-01 - 2027-04-30

The ongoing warming of the earth's climate due to man-made climate change is fundamentally changing our weather. Traditionally, weather forecasts have been made based on numerical models, so-called Numerical Weather Predictions (NWP). Data-driven machine learning models and in particular deep neural networks offer the potential as surrogate models for fast and (energy) efficient emulation of NWP models. As part of the SmartWeather21 project, we want to investigate which DL architecture for NWP is best suited for weather forecasting in a warmer climate, based on the high-resolution climate projections generated with ICON as part of WarmWorld. To incorporate the high resolutions of the WarmWorld climate projections, we will develop data- and model-parallel approaches and architectures for weather forecasting in a warmer climate. Furthermore, we will investigate which (learnable combinations of) variables from the ICON climate projections provide the best, physically plausible forecast accuracy for weather prediction in a warmer climate. With this in mind, we develop dimension reduction techniques for the various input variables that learn a latent, lower-dimensional representation based on the accuracy of the downstream weather forecast as an upstream task. The increased spatial resolution of the ICON simulations also allows conclusions to be drawn about the uncertainties of individual input and output variables at lower resolutions. As part of SmartWeather21, we will develop methods that parameterise these uncertainties using probability distributions and use them as input variables with lower spatial resolution in DL-based weather models. These can be propagated through the model as part of probabilistic forecasts.

EOSC Beyond

Contact: Jos van Wezel
Funding: EU
since 2024-04-01 - 2027-03-31

EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers

bwNET 2.0

Contact: Klara Mall
Funding: MWK
since 2024-04-01 - 2028-03-31
Project page: bwnet.belwue.de

Resilient, powerful and flexible network operation and the provision of individualized and secure network services are at the core of bwNET2.0. The aim is to contribute to fundamental research in the field of autonomous networks on the one hand and to design and implement concrete building blocks and mechanisms that can be used to further develop BelWü and campus networks on the other.

AI-enhanced differentiable Ray Tracer for Irradiation-prediction in Solar Tower Digital Twins - ARTIST

Contact: Dr. Marie Weiel, Dr. Markus Götz
Funding: Helmholtz-Gemeinschaft
since 2024-04-01 - 2026-03-31
Project page: www.helmholtz.ai/you-helmholtz-ai/project-funding

Solar tower power plants play a key role in facilitating the ongoing energy transition as they deliver dispatchable climate neutral electricity and direct heat for chemical processes. In this work we develop a heliostat-specific differentiable ray tracer capable of modeling the energy transport at the solar tower in a data-driven manner. This enables heliostat surface reconstruction and thus drastically improved the irradiance prediction. Additionally, such a ray tracer also drastically reduces the required data amount for the alignment calibration. In principle, this makes learning for a fully AI-operated solar tower feasible. The desired goal is to develop a holistic AI-enhanced digital twin of the solar power plant for design, control, prediction, and diagnosis, based on the physical differentiable ray tracer. Any operational parameter in the solar field influencing the energy transport may be, optimized with it. For the first time gradient-based, e.g., field design, aim point control, and current state diagnosis are possible. By extending it with AI-based optimization techniques and reinforcement learning algorithms, it should be possible to map real, dynamic environmental conditions with low-latency to the twin. Finally, due to the full differentiability, visual explanations for the operational action predictions are possible. The proposed AI-enhanced digital twin environment will be verified at a real power plant in Jülich. Its inception marks a significant step towards a fully automatic solar tower power plant.

Authentication and Authorisation for Research Collaboration Technical Revision to Enhance Effectiveness - AARC TREE

Contact: Dr. Marcus Hardt
Funding: EU
since 2024-03-01 - 2026-02-28
Project page: aarc-project.eu/aarc-tree-project

Collaboration and sharing of resources is critical for research. Authentication and Authorisation Infrastructures (AAIs) play a key role in enabling federated interoperable access to resources. The AARC Technical Revision to Enhance Effectiveness (AARC TREE) project takes the successful and globally recognised “Authentication and Authorisation for Research Collaboration” (AARC) model and its flagship outcome, the AARC Blueprint Architecture (BPA), as the basis to drive the next phase of integration for research infrastructures: expand federated access management to integrate user-centring technologies, expand access to federated data and services (authorisation), consolidating existing capacities and avoiding fragmentation and unnecessary duplication. SCCs participates in AARC-TREE to continue developing the Blueprint Architectures. Here we contribute to technical recommendations, as well as to policy development. Since SCC is also a core member of the IAM project of the german NFDI, we can raise the awareness of NFDI requirements in AARC, as well as feed new developments back to NFDI, in a very timely manner.

Holistic Imaging and Molecular Analysis in life-threatening Ailments - HIMALAYA

Contact: Dr. Charlotte Debus
Funding: BMBF
since 2024-02-01 - 2027-01-31

The overall goal of this project is to improve the radiological diagnosis of human prostate cancer in clinical MRI by AI-based exploitation of information from higher resolution modalities. We will use the brilliance of HiP-CT imaging at beamline 18 and an extended histopathology of the entire prostate to optimise the interpretation of MRI images in the context of a research prototype. In parallel, the correlation of the image data with the molecular properties of the tumours is planned for a better understanding of invasive tumour structures. An interactive multi-scale visualisation across all modalities forms the basis for vividly conveying the immense amounts of data. As a result, at the end of the three-year project phase, the conventional radiological application of magnetic resonance imaging (MRI) is to be transferred into a diagnostic standard that also reliably recognises patients with invasive prostate tumours that have often been incorrectly diagnosed to date, taking into account innovative AI algorithms. In the medium term, a substantial improvement in the care of patients with advanced prostate carcinoma can therefore be expected. In addition, we will make the unique multimodal data set created in the project, including visualisation tools, available as open data to enable further studies to better understand prostate cancer, which could potentially lead to novel diagnostic and therapeutic approaches.

bwHPC-S5: Scientific Simulation and Storage Support Services Phase 3 - bwHPC-S5 Phase 3

Contact: Dr. Robert Barthel
Funding: MWK
since 2023-11-01 - 2026-01-31
Project page: https://www.bwhpc.de

Zusammen mit den gewonnenen Erkenntnissen, Bewertungen und Empfehlungen sollen die aktuellen Herausforderungen und definierten Handlungsfelder des Rahmenkonzepts der Universitäten des Landes Baden-Württemberg für das HPC und DIC im Zeitraum 2025 bis 2032 durch folgende Maßnahmen im Projekt konkretisiert werden: • Weiterentwicklung der Wissenschaftsunterstützung bzgl. Kompetenzen zur Unterstützung neuartiger System- und Methodekonzepte (KI, ML oder Quantencomputing), Vernetzung mit Methodenfor- schung, ganzheitliche Bedarfsanalysen und Unterstützungsstrategien (z.B. Onboarding) • Steigerung der Energieeffizienz durch Sensibilisierung sowie Untersuchung und Einsatz neuer Be- triebsmodelle und Workflows inkl. optimierter Software • Erprobung und flexible Integration neuer Systemkomponenten und -architekturen, Ressourcen (z.B. Cloud) sowie Virtualisierung- und Containerisierungslösungen • Umsetzung neue Software-Strategien (z.B. Nachhaltigkeit und Entwicklungsprozesse) • Ausbau der Funktionalitäten der baden-württembergischen Datenföderation (z.B. Daten-Transfer- Service) • Umsetzung von Konzepten beim Umgang mit sensiblen Daten und zur Ausprägung einer digitalen Souveränität • Vernetzung und Kooperation mit anderen Forschungsinfrastrukturen

bwCloud 3

since 2023-09-01 - 2027-08-31
Project page: https://www.bw-cloud.org

Enhancement of bwCloud infrastructure (locations FR, KA, MA, UL). Adding further bwServices on it. (Predecessor of project bwCloud SCOPE)

ICON-SmART

Contact: Dr. Jörg Meyer
Funding: Hans-Ertel-Zentrum für Wetterforschung
since 2023-07-26 - 2027-07-25
Project page: www.hans-ertel-zentrum.de/Projekte/ICON-SmART.html

“ICON-SmART” addresses the role of aerosols and atmospheric chemistry for the simulation of seasonal to decadal climate variability and change. To this end, the project will enhance the capabilities of the coupled composition, weather and climate modelling system ICON-ART (ICON, icosahedral nonhydrostatic model – developed by DWD, MPI-M and DKRZ with the atmospheric composition module ART, aerosols and reactive trace gases – developed by KIT) for seasonal to decadal predictions and climate projections in seamless global to regional model configurations with ICON-Seamless-ART (ICON-SmART). Based on previous work, chemistry is a promising candidate for speed-up by machine learning. In addition, the project will explore machine learning approaches for other processes. The ICON-SmART model system will provide scientists, forecasters and policy-makers with a novel tool to investigate atmospheric composition in a changing climate and allows us to answer questions that have been previously out of reach.

Photonic materials with properties on demand designed with AI technology

Contact: Maria Paszkiewicz
Funding: NHR
since 2023-05-01
Project page: www.scc.kit.edu/forschung/15071.php

This project uses artificial neural networks in an inverse design problem of finding nano-structured materials with optical properties on demand. Achieving this goal requires generating large amounts of data from 3D simulations of Maxwell's equations, which makes this a data-intensive computing problem. Tailored algorithms are being developed that address both the learning process and the efficient inversion. The project complements research in the SDL Materials Science on AI methods, large data sets generated by simulations, and workflows.

Artificial intelligence for the Simulation of Severe AccidentS - ASSAS

since 2023-05-01 - 2026-10-31
Project page: assas-horizon-euratom.eu

The ASSAS project aims at developing a proof-of-concept SA (severe accident) simulator based on ASTEC (Accident Source Term Evaluation Code). The prototype basic-principle simulator will model a simplified generic Western-type pressurized light water reactor (PWR). It will have a graphical user interface to control the simulation and visualize the results. It will run in real-time and even much faster for some phases of the accident. The prototype will be able to show the main phenomena occurring during a SA, including in-vessel and ex-vessel phases. It is meant to train students, nuclear energy professionals and non-specialists. In addition to its direct use, the prototype will demonstrate the feasibility of developing different types of fast-running SA simulators, while keeping the accuracy of the underlying physical models. Thus, different computational solutions will be explored in parallel. Code optimisation and parallelisation will be implemented. Beside these reliable techniques, different machine-learning methods will be tested to develop fast surrogate models. This alternate path is riskier, but it could drastically enhance the performances of the code. A comprehensive review of ASTEC's structure and available algorithms will be performed to define the most relevant modelling strategies, which may include the replacement of specific calculations steps, entire modules of ASTEC or more global surrogate models. Solutions will be explored to extend the models developed for the PWR simulator to other reactor types and SA codes. The training data-base of SA sequences used for machine-learning will be made openly available. Developing an enhanced version of ASTEC and interfacing it with a commercial simulation environment will make it possible for the industry to develop engineering and full-scale simulators in the future. These can be used to design SA management guidelines, to develop new safety systems and to train operators to use them.

Energy Efficiency and Performance of AI at Scale - EPAIS

Contact: Dr. Charlotte Debus
Funding: NHR
since 2023-01-01 - 2024-06-30

With the rise of artificial intelligence and the accompanying demand in compute resources, the energy efficiency of large scale deep learning (DL) becomes increasingly important. The goal of EPAIS is to evaluate and correlate computational performance and energy consumption of state-of-the-art DL models at scale, and to improve the latter by optimising the former In this project, we measure and analyze energy consumption and computational performance of scientific DL workloads at scale intending to uncover the correlation between these two. Along these lines, we develop easy-to-use, low overhead tools for measuring energy consumption and performance. These tools can be incorporated by AI developers into their code for basic assessment of these metrics, fostering awareness for GreenAI and GreenHPC. Based on these insights, we develop new approaches to increase the energy efficiency of DL workloads through means of performance optimization.

Data and services to support marine and freshwater scientists and stakeholders - AquaINFRA

Contact: Dr. Jörg Meyer
Funding: EU
since 2023-01-01 - 2026-12-31
Project page: aquainfra.eu

The AquaINFRA project aims to develop a virtual environment equipped with FAIR multi-disciplinary data and services to support marine and freshwater scientists and stakeholders restoring healthy oceans, seas, coastal and inland waters. The AquaINFRA virtual environment will enable the target stakeholders to store, share, access, analyse and process research data and other research digital objects from their own discipline, across research infrastructures, disciplines and national borders leveraging on EOSC and the other existing operational dataspaces. Besides supporting the ongoing development of the EOSC as an overarching research infrastructure, AquaINFRA is addressing the specific need for enabling researchers from the marine and freshwater communities to work and collaborate across those two domains.

Implementation of an InfraStructure for dAta-BasEd Learning in environmental sciences - ISABEL

Contact: Dr. Jörg Meyer
Funding: DFG
since 2022-12-01 - 2025-11-30

The amount and diversity of digitally available environmental data is continuously increasing.  However, they are often hardly accessible or scientifically usable. The datasets frequently lack sufficient metadata description, are stored in a variety of data formats, and are still saved on local storage devices instead of data portals or repositories. Based on the virtual research environment V-FOR-WaTer, which was developed in a previous project, ISABEL aims at making this data abundance available in an easy-to-use web portal. Environmental scientists get access to data from different sources, e.g. state offices or university projects, and can share their own data through the portal. Integrated tools help to easily pre-process and scale the data and make them available in a consistent format. Further tools for more complex scientific analyses will be included. These are both implemented by the developers of the portal according to the requirements of the scientific community and contributed directly by the portal’s users. The possibility to store workflows together with the tools and respective data ensures reproducible data analysis. Additionally, interfaces with existing data repositories enable easy publication of the scientists’ data directly from the portal. ISABEL addresses the needs of researchers of hydrology and environmental science to not only find and access datasets but also conduct efficient data-based learning with standardised tools and reproducible workflows.

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DAPHONA

Contact: Dr. Jörg Meyer
Funding: BMBF
since 2022-12-01 - 2025-11-30
Project page: ../Projekte/daphona.html?nn=729750

Nano-optics deals with the optical properties of structures that are comparable to or smaller than the wavelength. All optical properties of a scatterer are determined by its T-matrix. Currently, these T-matrices are recalculated over and over again and are not used systematically. This wastes computing resources and does not allow novel questions to be addressed. DAPHONA remedies this deficiency. The project provides technologies with which the geometric and material properties of an object and its optical properties are brought together in a data structure. This data is systematically used to extract the T-matrix for a given object. It should also be possible to identify objects with predefined optical properties. Using these approaches, the DAPHONA project will answer novel questions that can only be addressed using this data-driven approach. The aim of the project is also to train young scientists at various qualification levels and to anchor the described approach in teaching. In addition, the data structure is to be coordinated within the specialist community. The data will be discussed in workshops and available methods for its use will be disseminated. The DAPHONA concept is open, based on the FAIR principles and will bring sustainable benefits to the entire community.

Skills for the European Open Science Commons: Creating a Training Ecosystem for Open and FAIR Science (Skills4EOSC)

Contact: Dr. Lisana Berberi
Funding: EU
since 2022-09-01 - 2025-08-31
Project page: www.skills4eosc.eu/

Skills4EOSC brings together leading experts from national, regional, institutional and thematic open science and data competence centers from 18 European countries with the aim of unifying the current training and education landscape into a common cross-European ecosystem to train researchers and data specialists from Europe at an accelerated pace in the fields of FAIR open data, data-intensive science and scientific data management.

Scalable and efficient uncertainty quantification for AI-based time series forecasting - EQUIPE

Contact: Dr. Charlotte Debus
Funding: BMBF
since 2022-09-01 - 2025-08-31

The EQUIPE project deals with the quantification of uncertainties in large transformer models for time series prediction. Although the transformer architecture is able to achieve astonishingly high prediction accuracy, it requires immense amounts of computational resources. Common approaches to error estimation in neural networks are equally computationally intensive, which currently makes their use in transformers considerably more difficult. The research work within EQUIPE aims to solve these problems and to develop scalable algorithms for quantifying uncertainties in large neural networks, which will enable the methods to be used in real-time systems in the future.

iMagine

Contact: Dr. Valentin Kozlov
Funding: EU
since 2022-09-01 - 2025-08-31
Project page: imagine-ai.eu

iMagine is an EU-funded project that provides a portfolio of ‘free at the point of use’ image datasets, high-performance image analysis tools empowered with Artificial Intelligence (AI), and Best Practice documents for scientific image analysis. These services and materials enable better and more efficient processing and analysis of imaging data in marine and freshwater research, relevant to the overarching theme of ‘Healthy oceans, seas, coastal and inland waters’.

Artificial Intelligence for the European Open Science Cloud - AI4EOSC

Contact: Dr. Valentin Kozlov
Funding: EU
since 2022-09-01 - 2025-08-31
Project page: ai4eosc.eu

The AI4EOSC (Artificial Intelligence for the European Open Science Cloud) is an EU-funded project that delivers an enhanced set of advanced services for the development of AI/ML/DL models and applications in the European Open Science Cloud (EOSC). These services are bundled together into a comprehensive platform providing advanced features such as distributed, federated and split learning; novel provenance metadata for AI/ML/DL models; event-driven data processing services. The project builds on top of the DEEP-Hybrid-DataCloud outcomes and the EOSC compute platform.

Development and validation of a hybrid grid/particle method for turbulent flows supported by high performance computations with OpenFOAM - hGVtSOF

Contact: Dr. Jordan Denev
Funding: NHR
since 2022-06-15 - 2025-06-14
Project page: scc.kit.edu/forschung/14972.php

The main goal of the present project is the further development and validation of a new computational fluid dynamics (CFD) method using a combination of grid-free (particles) and grid-based techniques. A fundamental assumption of this novel approach is the decomposition of any physical quantity into the grid based (large scale) and the fine scale parts, whereas large scales are resolved on the grid and fine scales are represented by particles. Dynamics of large and fine scales is calculated from two coupled transport equations one of which is solved on the grid whereas the second one utilizes the Lagrangian grid free Vortex Particle Method (VPM).

InterTwin

Contact: Dr. Marcus Hardt
Funding: EU
since 2022-06-01 - 2025-06-30
Project page: InterTwin.eu

InterTwin co-designs and implements the prototype of an interdisciplinary Digital Twin Engine (DTE), an open source platform that provides generic and tailored software components for modelling and simulation to integrate application- specific Digital Twins (DTs). Its specifications and implementation are based on a co-designed conceptual model - the DTE blueprint architecture - guided by the principles of open standards and interoperability. The ambition is to develop a common approach to the implementation of DTs that is applicable across the whole spectrum of scientific disciplines and beyond to facilitate developments and collaboration.

Gaia-X4 for the Innovations Campus Future Mobility - Gaia-X4ICM

Contact: Klaus Scheibenberger
Funding: MWK
since 2022-06-01 - 2024-12-31
Project page: www.icm-bw.de

The Gaia-X is an European initiative that aims to provide a secure and trustworthy platform for data sharing and collaboration across various industries and sectors in Europe. One of the main goals of the Gaia-X4ICM research initiative for the Innovations Campus Future Mobility (ICM) is to create the basic infrastructure with all necessary hardware and software components that play a significant role in connecting various sectors involved in an industrial production process. The SCC builds and runs such a cloud infrastructure that operates on our own hardware retaining control over the digital infrastructure and data – ensuring data sovereignty, privacy and security.

Materialized holiness - toRoll

Contact: Dr. Danah Tonne
Funding: BMBF
since 2022-04-01 - 2026-03-31
Project page: geschkult.fu-berlin.de/e/materialisierte-heiligkeit

In the project "Materialized Holiness" Torah scrolls are studied as an extraordinary codicological, theological and social phenomenon. Unlike, for example, copies of the Bible, the copying of sacred scrolls has been governed by strict regulations since antiquity and is complemented by a rich commentary literature. Together with experts in Jewish studies, materials research, and the social sciences, we would like to build a digital repository of knowledge that does justice to the complexity of this research subject. Jewish scribal literature with English translations, material analyses, paleographic studies of medieval Torah scrolls, as well as interview and film material on scribes of the present day are to be brought together in a unique collection and examined in an interdisciplinary manner for the first time. In addition, a 'virtual Torah scroll' to be developed will reveal minute paleographic details of the script and its significance in cultural memory.

Metaphors of Religion - SFB1475

Contact: Dr. Danah Tonne
Funding: DFG
since 2022-01-01 - 2025-12-31
Project page: sfb1475.ruhr-uni-bochum.de

The SFB 1475, located at the Ruhr-Universität Bochum (RUB), aims to understand and methodically record the religious use of metaphors across times and cultures. To this end, the subprojects examine a variety of scriptures from Christianity, Islam, Judaism, Zoroastrianism, Jainism, Buddhism, and Daoism, originating from Europe, the Near and Middle East, as well as South, Central, and East Asia, and spanning the period from 3000 BC to the present. For the first time, comparative studies on a unique scale are made possible through this collaborative effort. Within the Collaborative Research Center, the SCC, together with colleagues from the Center for the Study of Religions (CERES) and the RUB, is leading the information infrastructure project "Metaphor Base Camp", in which the digital data infrastructure for all subprojects is being developed. The central component will be a research data repository with state-of-the-art annotation, analysis and visualization tools for the humanities data. Translated with www.DeepL.com/Translator (free version)

Helmholtz Platform for Research Software Engineering - Preparatory Study (HiRSE_PS)

Contact: Prof. Dr. Achim Streit (Projektkoordinator)
Funding: Helmholtz-Gemeinschaft
since 2022-01-01 - 2024-12-31
Project page: www.helmholtz-hirse.de

The HiRSE concept sees the establishment of central activities in RSE and the targeted sustainable funding of strategically important codes by so-called Community Software Infrastructure (CSI) groups as mutually supportive aspects of a single entity.

Sustainable concepts for the campus networks of universities in BW - bwCampusnetz

Contact: Klara Mall
Funding: MWK
since 2021-12-01 - 2025-12-31
Project page: bwcampusnetz.de

In the bwCampusnetz project, several universities in Baden-Württemberg are working together to shed light on university campus networks away from the constraints of day-to-day business, but still very close to the realities of operation. Future-proof concepts are to be found and their practical feasibility is to be investigated and demonstrated through prototypical implementations.

PUNCH4NFDI

Contact: Dr. Manuel Giffels
Funding: DFG
since 2021-10-01 - 2026-09-30
Project page: www.punch4nfdi.de

PUNCH4NFDI is the NFDI consortium of particle, astro-, astroparticle, hadron and nuclear physics, representing about 9.000 scientists with a Ph.D. in Germany, from universities, the Max Planck society, the Leibniz Association, and the Helmholtz Association. PUNCH physics addresses the fundamental constituents of matter and their interactions, as well as their role for the development of the largest structures in the universe - stars and galaxies. The achievements of PUNCH science range from the discovery of the Higgs boson over the installation of a 1 cubic kilometer particle detector for neutrino detection in the antarctic ice to the detection of the quark-gluon plasma in heavy-ion collisions and the first picture ever of the black hole at the heart of the Milky Way. The prime goal of PUNCH4NFDI is the setup of a federated and "FAIR" science data platform, offering the infrastructures and interfaces necessary for the access to and use of data and computing resources of the involved communities and beyond. The SCC plays a leading role in the development of the highly distributed Compute4PUNCH infrastructure and is involved in the activities around Storage4PUNCH a distributed storage infrastructure for the PUNCH communities.

NFDI-MatWerk

Contact: Prof. Dr. Achim Streit
Funding: DFG
since 2021-10-01 - 2026-09-30
Project page: nfdi-matwerk.de

The NFDI-MatWerk consortium receives a five-year grant within the framework of the National Research Data Infrastructure (NFDI) for the development of a joint materials research data space. NFDI-MatWerk stands for Materials Science and Engineering to characterize the physical mechanisms in materials and develop resource-efficient high-performance materials with the most ideal properties for the respective application. Data from scientific groups distributed across Germany are to be able to be addressed via a knowledge-graph-based infrastructure in such a way that fast and complex search queries and evaluations become possible. At KIT, the Scientific Computing Center (SCC) and the Institute for Applied Materials (IAM) are involved. In the SCC, we will establish the Digital Materials Environment with the infrastructure services for the research data and their metadata together with the partners.

bwIDM-Security and Community

Contact: Ulrich Weiß
Funding: MWK
since 2021-08-01 - 2024-12-31
Project page: www.bwidm.de

The outlined project bwIDM2 is dedicated to the increased demands on IT security and takes into account current technical developments. It creates the prerequisites for the integration of services across higher education institutions and establishes a group/role administration for supraregional and national communities with delegation mechanisms. In addition, specialist concepts for the integration of a long-term person identifier in bwIDM, as required for use in research data management, are being developed.

Numerical modeling of cardiac electrophysiology at the cellular scale - MICROCARD

Contact: Prof. Dr. Hartwig Anzt
Funding: BMBF / EU
since 2021-04-01 - 2024-10-01
Project page: microcard.eu

Cardiovascular diseases are among the most common causes of death worldwide: Every year, more than 300,000 people die in Germany as a result. Around half of these deaths are caused by cardiac arrhythmias. In the European MICROCARD project, in which the Karlsruhe Institute of Technology (KIT) is involved, researchers are now developing a simulation platform that can digitally map the electrophysical signal transmissions in the heart. The computer simulations are to contribute in particular to improved diagnosis and therapy. KIT will receive about 1.3 million euros for its contributions within the framework of the "European High-Performance Computing Joint Undertaking".

NFFA Europe Pilot - NEP

Contact: Rosella Aversa
Funding: EU
since 2021-03-01 - 2026-02-28
Project page: https://www.nffa.eu

NEP provides important resources for nanoscientific research and develop new cooperative working methods. The use of innovative research data and metadata management technologies is becoming increasingly important. In the NEP project, the SCC contributes with new methods for metadata enrichment, development of large data collections, and the provision of virtual services to the establishment of a joint research data infrastructure.

Joint Lab VMD - JL-VMD

Contact: Dr. Ivan Kondov
Funding: BMBF
since 2021-01-01
Project page: Virtual Materials Design (VirtMat)

Within the Joint Lab VMD, the SDL Materials Science develops methods, tools and architectural concepts for supercomputing and big data infrastructures, which are tailored to tackle the specific application challenges and to facilitate the digitalization in materials research and the creation of digital twins. In particular, the Joint Lab develops a virtual research environment (VRE) that integrates computing and data storage resources in existing workflow managements systems and interactive environments for simulation and data analyses.

Joint Lab MDMC - JL-MDMC

since 2021-01-01
Project page: Joint Lab MDMC

Within the framework of the Joint Lab "Integrated Model and Data Driven Materials Characterization" (MDMC), the SDL Materials Science is developing a concept for a data and information platform to make data on materials available in a knowledge-oriented way as an experimental basis for digital twins and for the development of simulation-based methods for predicting material structure and properties. It defines a metadata model to describe samples and datasets from experimental measurements and harmonizes data models for material simulation and correlative characterization using materials science vocabularies and ontologies.

NFDI4Ing

Contact: Prof. Dr. Achim Streit
Funding: DFG
since 2020-10-01 - 2025-09-30
Project page: nfdi4ing.de

NFDI4Ing is a consortium of engineering sciences and promotes the management of technical research data. NFDI4Ing was founded back in 2017 and is in close exchange with researchers from all engineering disciplines. The consortium offers a unique method-oriented and user-centered approach to make technical research data FAIR - discoverable, accessible, interoperable, and reusable. An important challenge here is the large number of sub-disciplines in engineering and their subject-specific peculiarities. KIT is involved with a co-spokesperson, Britta Nestler from the Institute for Applied Materials (IAM) and a co-spokesperson, Achim Streit from the Scientific Computing Center (SCC). As part of NFDI4Ing, the SCC is developing and implementing the concepts for federated research data infrastructures, data management processes, repositories and metadata management in close cooperation with the partners. The NFDI4Ing application https://doi.org/10.5281/zenodo.4015200 describes the planned research data infrastructure in detail. Translated with www.DeepL.com/Translator (free version)

NFDI4Chem Chemistry Consortium in the NFDI

Contact: Dr. Doris Ressmann
Funding: DFG
since 2020-10-01 - 2025-09-30
Project page: nfdi4chem.de

The vision of NFDI4Chem is the digitization of all work processes in chemical research. To this end, infrastructure is to be established and expanded to support researchers in collecting, storing and archiving, processing and analyzing research data, as well as publishing the data in repositories together with descriptive metadata and DOIs, thus making them referencable and reusable. As a professional consortium, NFDI4Chem represents all disciplines of chemistry and works closely with the major professional societies to this end. Translated with www.DeepL.com/Translator (free version)

Episteme in motion - SFB 980

Contact: Dr. Danah Tonne
Funding: DFG
since 2020-07-01 - 2024-06-30
Project page: sfb-episteme.de

The Collaborative Research Centre 980 'Episteme in Motion' has been investigating processes of knowledge change in European and non-European cultures from the 3rd millennium BC to around 1750 AD since 2012. Since 2016, the SCC has been supporting the collection of digital evidence for previously unresolved questions through its expertise in modern research data management. In the subproject Information Infrastructure, SCC develops information technology procedures for data indexing for the investigation and visualization of knowledge movements in long-term traditional pre-modern knowledge stocks using the example of travels of manuscripts, prints as well as coffin and pyramid text sayings. Based on a research data repository, (1) new tools for data analysis, (2) specific vocabulary services and (3) innovative presentation layers will be developed. With the collaboration at three locations (Berlin, Karlsruhe, Darmstadt), the project has a pilot function with regard to the establishment of complex institutional collaborations in the field of research data management. translated with DeepL.com

HAICORE

Contact: Dr. Markus Götz
Funding: Helmholtz-Gemeinschaft

The Helmholtz AI COmpute REssources (HAICORE) infrastructure project was launched in early 2020 as part of the Helmholtz Incubator "Information & Data Science" to provide high-performance computing resources for artificial intelligence (AI) researchers in the Helmholtz Association. Technically, the AI hardware is operated as part of the high-performance computing systems JUWELS (Julich Supercomputing Centre) and HoreKa (KIT) at the two centers. The SCC primarily covers prototypical development operations in which new approaches, models and methods can be developed and tested. HAICORE is open to all members of the Helmholtz Association in the field of AI research.

Helmholtz Metadata Collaboration Platform - HMC

Contact: Dr. Rainer Stotzka
Funding: Helmholtz-Gemeinschaft
since 2019-10-01 - 2024-09-30
Project page: helmholtz-metadaten.de

With the Helmholtz Metadata Collaboration Platform, an important topic area of the Helmholtz Incubator "Information & Data Science" was launched at the end of 2019, bringing together the expertise of Helmholtz centers and shaping the topic of "Information & Data Science" across the boundaries of centers and research fields. The overarching goal of the platform is to advance the qualitative enrichment of research data through me-tadata in the long term, to support researchers - and to implement this in the Helmholtz Association and beyond. With the work package FAIR Data Commons Technologies, SCC develops technologies and processes to make research data from the research fields of the Helmholtz Association and beyond available to researchers according to the FAIR principles. This is achieved on a technical level by providing uniform access to metadata using standardized interfaces that are based on recommendations and standards adopted by consensus within globally networked research data initiatives, e.g., the Research Data Alliance (RDA, https://www.rd-alliance.org/). For researchers, these interfaces are made usable through easy-to-use tools, generally applicable processes and recommendations for handling research data in everyday scientific life.

Helmholtz AI

Contact: Dr. Markus Götz
Funding: Helmholtz-Gemeinschaft
since 2019-04-01
Project page: www.helmholtz.ai

The Helmholtz AI Platform is a research project of the Helmholtz Incubator "Information & Data Science". The overall mission of the platform is the "democratization of AI for a data-driven future" and aims at making AI algorithms and approaches available to a broad user group in an easy-to-use and resource-efficient way. (Translated with DeepL.com)

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RTG 2450 - Taylored Scale-Bridging Approaches to Computational Nanoscience - GRK 2450 (DFG)

since 2019-04-01 - 2028-03-31
Project page: www.compnano.kit.edu

In the Research Training Group Tailored Scale-Bridging Approaches to Computational Nanoscience we investigate problems, that are not tractable by computational chemistry standard tools. The research is organized in seven projects. Five projects address scientific challenges such as friction, materials aging, material design and biological function. In two further projects, new methods and tools in mathematics and computer science are developed and provided for the special requirements of these applications. The SCC is involved in projects P4. P5 and P6.

Helmholtz Federated IT Services - HIFIS

since 2019-01-01
Project page: www.hifis.net

Helmholtz Federated IT Services (HIFIS) establishes a secure and easy-to-use collaborative environment with ICT services that are efficient and accessible from anywhere. HIFIS also supports the development of research software with a high level of quality, visibility and sustainability.

Simulated worlds

Contact: Prof. Dr. Martin Frank
Funding: MWK
since 2018-07-01 - 2024-08-31
Project page: simulierte-welten.de

The Simulated Worlds project aims to provide students in Baden-Württemberg with a deeper critical understanding of the possibilities and limitations of computer simulations. The project is jointly supported by the Scientific Computing Center (SCC), the High Performance Computing Center Stuttgart (HLRS) and the University of Ulm and is already working with several schools in Baden-Württemberg.

Computational and Mathematical Modeling Program - CAMMP

Contact: Prof. Dr. Martin Frank
Funding: MWK
since 2015-01-01 - 2024-08-31
Project page: forschung/CAMMP

CAMMP stands for Computational and Mathematical Modeling Program. It is an extracurricular offer of KIT for students of different ages. We want to make the public aware of the social importance of mathematics and simulation sciences. For this purpose, students actively engage in problem solving with the help of mathematical modeling and computer use in various event formats together with teachers. In doing so, they explore real problems from everyday life, industry or research.

Finished Projects

A new TEstbed for Exploring Machine LEarning in Atmospheric Prediction - TEEMLEAP

Contact: Dr. Jörg Meyer
Funding: KIT-Exzellenzinitiative
since 2021-09-01 - 2023-08-30
Project page: www.imk-tro.kit.edu/5877_11188.php

Despite steady improvements in numerical weather prediction models, they still exhibit systematic errors caused by simplified representations of physical processes, assumptions about linear behavior, and the challenges of integrating all available observational data. Weather services around the world now recognize that addressing these shortcomings through the use of artificial intelligence (AI) could revolutionize the discipline in the coming decades. This will require a fundamental shift in thinking that integrates meteorology much more closely with mathematics and computer science. TEEMLEAP will foster this cultural change through a collaboration of scientists from the KIT Climate and Environment and MathSEE centers by establishing an idealized testbed to explore machine learning in weather forecasting. In contrast to weather services, which naturally focus on improvements of numerical forecast models in their full complexity, TEEMLEAP intends to evaluate the application possibilities and benefits of AI in this testbed along the entire process chain of weather forecasting.

EOSC Future

Contact: Jos van Wezel
Funding: EU
since 2021-04-01 - 2024-03-31
Project page: https://eoscfuture.eu

EOSC Future responds to INFRAEOSC-03-2020 call in order to integrate, consolidate, and connect e-infrastructures, research communities, and initiatives in Open Science to further develop the EOSC Portal, EOSC-Core and EOSCExchange of the European Open Science Cloud (EOSC).

bwHPC-S5: Scientific Simulation and Storage Support Services - bwHPC-S5 Phase 2

Contact: Dr. Robert Barthel
Funding: MWK
since 2021-04-01 - 2023-10-31
Project page: www.bwhpc.de

The primary objective of the project is to establish an integrated nationwide computing and data infrastructure and to increase efficiency and effectiveness by providing first-class support to scientists and users.

EGI Advanced Computing for EOSC - EGI-ACE

Contact: Dr. Pavel Weber
Funding: EU
since 2021-01-01 - 2023-06-30

EGI-ACE empowers researchers from all disciplines to collaborate in data- and compute-intensive research across borders through free at point of use services. Building on the distributed computing integration in EOSChub, it delivers the EOSC Compute Platform and contributes to the EOSC Data Commons through a federation of Cloud compute and storage facilities, PaaS services and data spaces with analytics tools and federated access services. The Platform is built on the EGI Federation, the largest distributed computing infrastructure for research. The EGI Federation delivers over 1 Exabyte of research data and 1 Million CPU cores which supported the discovery of the Higgs Boson and the first observation of gravitational waves, while remaining open to new members. The Platform pools the capacity of some of Europe’s largest research data centres, leveraging ISO compliant federated service management. Over 30 months, it will provide more than 82 M CPU hours and 250 K GPU hours for data processing and analytics, and 45 PB/month to host and exploit research data. Its services address the needs of major research infrastructures and communities of practice engaged through the EOSC-hub project. The Platform advances beyond the state of the art through a data-centric approach, where data, tools and compute and storage facilities form a fully integrated environment accessible across borders thanks to Virtual Access. The Platform offers heterogeneous systems to meet different needs, including state of the art GPGPUs and accelerators supporting AI and ML, making the Platform an ideal innovation space for AI applications. The data spaces and analytics tools are delivered in collaboration with tens of research infrastructures and projects, to support use cases for Health, the Green Deal, and fundamental sciences. The consortium builds on the expertise and assets of the EGI federation members, key research communities and data providers, and collaborating initiatives.

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Data Infrastructure Capacity for EOSC - DICE

Contact: Dr. Pavel Weber
Funding: EU
since 2021-01-01 - 2023-06-30
Project page: www.dice-eosc.eu

The Data Infrastructure Capacities for EOSC (DICE) consortium brings together a network of computing and data centres, research infrastructures, and data repositories for the purpose to enable a European storage and data management infrastructure for EOSC, providing generic services and building blocks to store, find, access and process data in a consistent and persistent way. Specifically, DICE partners will offer 14 state-of-the-art data management services together with more than 50 PB of storage capacity. The service and resource provisioning will be accompanied by enhancing the current service offering in order to fill the gaps still present to the support of the entire research data lifecycle; solutions will be provided for increasing the quality of data and their re-usability, supporting long term preservation, managing sensitive data, and bridging between data and computing resources. All services provided via DICE will be offered through the EOSC Portal and interoperable with EOSC Core via a lean interoperability layer to allow efficient resource provisioning from the very beginning of the project. The partners will closely monitor the evolution of the EOSC interoperability framework and guidelines to comply with a) the rules of participation to onboard services into EOSC, and b) the interoperability guidelines to integrate with the EOSC Core functions. The data services offered via DICE through EOSC are designed to be agnostic to the scientific domains in order to be multidisciplinary and to fulfil the needs of different communities. The consortium aims to demonstrate their effectiveness of the service offering by integrating services with community platforms as part of the project and by engaging with new communities coming through EOSC.

Smart Research Data Management to facilitate Artificial Intelligence in Climate and Environmental Sciences - SmaRD-AI

Contact: Dr. Marcus Strobl
Funding: KIT-Exzellenzinitiative
since 2020-06-01 - 2022-11-30
Project page: www.klima-umwelt.kit.edu/1226_1228

Research data management forms the basis for applying, for example, modern artificial intelligence methods to research questions. Therefore, research data management is an important component of the KIT Climate and Environment Center. In the SmaRD-AI project (short for Smart Research Data Management to facilitate Artificial Intelligence in Climate and Environmental Sciences), the IWG, IMK, GIK, and SCC at KIT are working closely together not only to make the treasure trove of climate and environmental data available at KIT accessible, but also to be able to analyze it in a structured way using tools. Translated with DeepL

bwNET2020+ for a more powerful and versatile network in Baden-Württemberg

Contact: Philipp Wolter
Funding: MWK
since 2020-01-01 - 2023-12-31
Project page: bwnet.belwue.de

The bwNET2020+ project is intended to support the expansion of the state university network and innovation within the university networks, as the consolidation of IT services at universities places higher demands on the underlying network.

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Exascale Earth System Modeling - ExaESM

Contact: Dr. Jörg Meyer, Dr. Ole Kirner
Funding: Helmholtz-Gemeinschaft
since 2019-10-01 - 2021-09-01

The Exascale Earth System Modelling (PL-ExaESM) pilot lab explores specific concepts for applying Earth System models and their workflows to future exascale supercomputers.

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EOSC-Synergy

Contact: Dr. Marcus Hardt
Funding: EU
since 2019-09-01 - 2022-10-31
Project page: www.eosc-synergy.eu

The EOSC Synergy project aims to expand the European Open Science Cloud (EOSC). A team of 25 engineers and scientists will work on the expansion of the European Open Science Cloud (EOSC) by integrating National and Scientific Infrastructures.

EOSC Pillar - EOSC-Pillar

Contact: Jos van Wezel
Funding: EU
since 2019-07-01 - 2022-12-31
Project page: www.eosc-pillar.eu

EOSC-Pillar will coordinate national Open Science efforts across Austria, Belgium, France, Germany and Italy, and ensure their contribution and readiness for the implementation of the EOSC.

OCR-D Successor Proposal 2018

Contact: Dr. Rainer Stotzka
Funding: DFG
since 2019-04-01 - 2020-06-30
Project page: ocr-d.de

OCR-D is a coordination project of the German Research Foundation (DFG) for the further development of Optical Character Recognition techniques for German-language prints of the 16th-19th century. The main goal is the full text capture of the cultural heritage printed in German-language of this period.

bwIPv6@Academia

Contact: Klara Mall
Funding: MWK
since 2019-04-01 - 2021-12-31
Project page: bwipv6.de

Das Landesprojekt bwIPv6@Academia hat die Aufgabe, den Zustand der IPv6-Fähigkeit gemeinsam mit den teilnehmenden Einrichtungen zu analysieren, Probleme und Aufgaben zu identifizieren, sowie die Umsetzung zu begleiten.

GÉANT Project GN4-3

Contact: Dr. Marcus Hardt
Funding: EU / DFN
since 2019-01-01 - 2022-12-31
Project page: www.geant.org/Projects/GEANT_Project_GN4-3

The GÉANT Project has gro​wn during its iterations (GN1, GN2, GN3, GN3plus, GN4-1 and GN4-2) to incorporate not just the award-winning 500Gbps pan-European network, but also a catalogue of advanced, user-focused services, and a successful programme of innovation that is pushing the boundaries of networking technology to deliver real impact to over 50 million users.

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EOSCsecretariat.eu

Contact: Jos van Wezel
Funding: EU
since 2019-01-01 - 2021-05-30
Project page: www.eoscsecretariat.eu

SCC is a prominent partner in the EOSC-secretariat.eu, supporting governance for EOSC while working with communities towards an all-encompassing European Open Science Cloud.

bwCard - Baden-Württemberg Smart Card Federation

Contact: Axel Maurer, Gabriele Schramm
Funding: MWK
since 2018-12-01 - 2021-11-30
Project page: www.bwcard.de

The bwCard project is carried out by the universities of the state of Baden-Württemberg. The aim is to create a federation that enables the participating institutions to reliably integrate chip cards from the other institution into their own digital processes and services.

Helmholtz Metadata & Knowledge System HGF ZT-I-PS-03-2

Contact: Dr. Rainer Stotzka
Funding: (ungeklärt)
since 2018-03-01 - 2020-02-29

Förderung Inkubator HMC Projektantrag durch HGF IVF

EOSC-hub

Contact: Dr. Pavel Weber
Funding: EU
since 2018-01-01 - 2021-12-31
Project page: www.eosc-hub.eu

EOSC-hub möchte u. a. einen einfachen Zugang zu hochqualitativen digitalen Diensten schaffen, die von den pan-europäischen Partnern in einem offenen Service-Katalog angeboten werden.

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Deep Hybrid Data Cloud - DHDC / DEEP

Contact: Dr. Marcus Hardt
Funding: EU
since 2017-11-01 - 2020-04-30
Project page: deep-hybrid-datacloud.eu

The DHDC project investigates how to support compute-intensive applications that require high-performance computing (HPC) and graphics processors (GPUs) with the help of cloud services.

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Helmholtz Analytics Framework (HAF)

Contact: Prof. Dr. Achim Streit
Funding: Helmholtz-Gemeinschaft
since 2017-10-01 - 2021-03-31
Project page: www.helmholtz-analytics.de/

The Helmholtz Analytics Framework (HAF) pilot project will strengthen the development of data sciences in the Helmholtz Association. Together with four other Helmholtz Centres, a co-design approach between domain scientists and data analysis experts investigates challenging application problems from the respective Helmholtz Centres. Specifically, these are questions on earth system modelling, structural biology, aerospace, neurosciences and medical imaging.

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Numerische Simulation von Schwerinonenstrahlen mittels Minimum-Entropie-Rekonstruktion - Shine

since 2017-09-01 - 2020-12-31

Ziel des Projekts ist die Entwicklung von neuen Werkzeugen zur Simulation von Schwerionenstrahlen in Targets. Wir möchten die Orts- und Energieverteilung aller Primär- und Sekundärteilchen charakterisieren. Dies ist von Interesse in vielen Feldern: Atomphysik (atomare Wechselwirkung, Ioneneinfang), Kernphysik (Untersuchung der Struktur von Atomkernen), Elektronik (Ablagerung von Elementen), Materialwissenschaften (Analyse von Beschädigungen z.B. eines Tokamaks), Biologie (Untersuchung der Toxikologie von Gewebe durch Ionenanalyse). Die Simulation von schweren Ionen ist schwierig aus zwei Gründen: Zum einen ist die gitterbasierte Simulation von Teilchentransport sehr herausfordernd. Zum anderen basieren die Simulationen auf Messungen der Bremsvermögen der Ionen, und müssen daher als unsicher angesehen werden. Daher entwickeln wir ein neues, Entropie-basiertes Diskretisierungsschema, welches eine Sub-Auflösung unterhalb des numerischen Gitters ermöglicht, und daher geeignet für die Simulation von Strahlen ist. Zusätzlich benutzen wir eine ähnliche Methode zur Behandlung von Unsicherheiten in der Teilchenverteilung, die durch die unsicheren Wirkungsquerschnitte bedingt werden. Unsere Methode ist rechenaufwändig, aber hochgradig parallelisierbar, was sie ideal für moderne Rechnerarchitekturen macht.

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OCR-D

Contact: Dr. Rainer Stotzka
Funding: DFG
since 2017-08-15 - 2018-12-31
Project page: ocr-d.de

OCR-D is a coordination project of the German Research Foundation (DFG) for the further development of Optical Character Recognition techniques for German-language prints of the 16th-19th century. The main goal is the full text capture of the cultural heritage printed in German-language of this period.

Authentiation and Authorisation for Research and Collaboration (AARC)

Contact: Dr. Marcus Hardt
Funding: EU
since 2017-05-01 - 2019-04-30
Project page: 10822.php

The EU-Project AARC aims to develop and pilot an integrated cross-discipline authentication and authorisation framework, built on existing AAIs and on production federated infrastructures.

Further development of the bwSync&Share service in Baden-Württemberg

Contact: Thomas Brandel
Funding: MWK
since 2017-01-01 - 2019-12-31
Project page: www.alwr-bw.de/dienste-der-beteiligten-einrichtungen/bwsyncshare

The state service bwSync&Share is an online storage service for employees and students of universities and colleges in Baden-Württemberg.

Helmholtz Data Federation - HDF

Contact: Prof. Dr. Achim Streit
Funding: Helmholtz-Gemeinschaft
since 2017-01-01 - 2021-12-31
Project page: www.helmholtz.de/hdf/

The Helmholtz Data Federation (HDF) is a strategic initiative of the Helmholtz Association that addresses one of the major challenges of the next decade: Managing the flood of data in science, especially from the large research infrastructures of the Helmholtz centers. (Translated with DeepL.com)

bwCloud - The Baden-Württemberg Cloud - bwCloud SCOPE

Contact: Matthias Leander-Knoll
Funding: MWK
since 2017-01-01 - 2019-12-31
Project page: www.bw-cloud.org

The Baden-Württemberg Cloud provides teaching and research institutions in the state with virtual machines that can be used like corresponding offerings from commercial providers without a lengthy application process.

Non-Destructive Analysis of Environmental Samples - ZEBRA

since 2016-11-15 - 2020-12-31
Project page: www.nuclear-training.de/forschungsprojekte-details/zebra.html

Development of an innovative measurement system based on P&DGNAA technology for environmental analysis including new evaluation algorithms.

Virtual research environment for water and terrestrial environmental research - V-For-WaTer

Contact: Dr. Jörg Meyer
Funding: MWK
since 2016-07-01 - 2018-06-30
Project page: www.vforwater.de

The project V-FOR-WaTer - Virtuelle Forschungsumgebung für die Wasser- und terrestrische Umweltforschung im Rahmen des Netzwerks Wasserforschung Baden-Württemberg - aims to create a virtual research environment (VRE), which will combine research data gathered in universities, research centres and from continuous monitoring of state offices in Baden-Württemberg into one comprehensive system. Facilitating access to all these different data sources in one system greatly reduces pre-processing time of complex analyses and enables the study of this extensive dataset towards the develop­ment a unified environmental system theory. The project is a co-operation between the SCC and the IWG.

ADA-FS - Advanced Data Placement via Ad-hoc File Systems at Extreme Scales

since 2016-04-01 - 2019-03-31

Future exascale HPC systems require efficient data management methods. The locality of data and the efficient access during a simulation are of great importance.

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Development of a decentralized electronic laboratory notebook - EDEL

Contact: Jan Potthoff, Veronika Leonhardt
Funding: DFG
since 2016-01-01 - 2019-12-31
Project page: chemotion.net

By developing a decentralized electronic laboratory book, researchers and scientists at KIT will in the future also use many advantages of digitization in laboratory documentation.

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bwDIM - Data in Motion

Contact: Dr. Felix Bach
Funding: MWK
since 2016-01-01 - 2018-06-30

The state project bwDataInMotion (bwDIM) supports scientists at universities in Baden-Württemberg in research data management. Its goal is to simplify the flow of data between the different systems.

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bwITsec – development of a cooperative IT security structure for the universities of Baden-Wuerttemberg - bwITSec

Contact: Andreas Lorenz
Funding: MWK
since 2015-10-01 - 2017-12-31

This project strives to design a state-wide outlined IT security concept as well as a federated IT security structure for the state of Baden-Wuerttemberg. Furthermore, a plan to implement a CERT structure for the state universities will be developed.

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Smart Data Innovation Lab (SDIL)

Contact: Andreas Petzold
Funding: MWK
since 2015-09-01 - 2018-08-31
Project page: www.sdil.de

The Scientific Computing Center (SCC) operates the research platform Smart Data Innovation Lab (SDIL) at KIT. SDIL creates the conditions for cutting-edge research in the field of Big Data ...

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INDIGO-DataCloud

Contact: Dr. Marcus Hardt
Funding: EU
since 2015-04-01 - 2017-09-30
Project page: www.indigo-datacloud.eu

The Project develops solutions for missing components in current Grid and Cloud Middleware. SCC works on components for the federated authentication and authorization as well as on the integration of archive systems in the distributed data management.

Metadata Management for Applied Sciences ( MASi)

Contact: Dr. Rainer Stotzka
Funding: DFG
since 2015-03-01 - 2019-06-30

Nowadays, an ever increasing amount of data is to be seen or expected in science. There is a great potential to gain new insights in various scientific fields by using this data efficiently. The drawback is the also ever increasing complexity and amount of the data and therefore the larger effort put on scientists in their daily work. Methods for data processing, which could be used in the past efficiently, might simply become impractical by failing to process large amounts of data in a given time and new methods need to be adopted or developed. In this project a novel and generic metadata management for scientific data will be developed based on an application-oriented description via metadata. The development process is accompanied by applied scientists from various and heterogeneous domains. The metadata management not only supports the data handling, but also allows an efficient use of provided scientific infrastructures. This infrastructure is going to be realized between the computing facilities of Dresden and Karlsruhe to provide generic and distributed services for metadata-based data handling. The management includes functionalities for data description, sustainable data storage, improved information retrieval, preparation for further processing and usage of available data.

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EUDAT2020

Contact: Jos van Wezel
Funding: EU
since 2015-03-01 - 2018-02-28
Project page: eudat.eu/projects/eudat2020

EUDAT - the collaborative Pan-European infrastructure providing research data services, training and consultancy for Researchers Research Communities Research Infrastructures & Data Centres

Smart Data Solution Center Baden-Württemberg - SDSC

Contact: Dr. Nico Schlitter
Funding: MWK
since 2014-10-01 - 2017-09-30
Project page: www.sdsc-bw.de

The SCC intensifies its Smart Data activities and starts together with the TECO research group at KIT and the SICOS-BW GmbH in Stuttgart the Smart Data Solution Center Baden-Württemberg (SDSC-BW). This research project is funded by the state of Baden-Württemberg and supports regional medium-sized companies in identifying the potential of innovative Smart Data technologies.

PolyEnergyNet - Resilient polygrids for secure energy supply - PEN

Contact: Dr. Matthias Bonn
Funding: BMWI
since 2014-09-01 - 2017-08-31

In the PolyEnergyNet project, resilient local grids are being researched and implemented as examples. In addition to the electricity grid as the "control grid," heat and gas grids with different types of generators, storage facilities and consumers also interact.

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National Hosting of Electronic Resources (NatHosting)

Contact: Till Neudecker
Funding: DFG
since 2014-02-01 - 2016-01-31

A reliable and sustainable access to scientific publications is a key requirement for research. Publications are normally accessed by retrieving a digital copy directly from the publisher’s or content provider’s homepages. This access can be disrupted due to several reasons such as a temporary failure of the publisher’s infrastructure, ceased operation of the publisher or simply cancellation of the subscription by the library. The project “National Hosting of Electronic Resources” develops a concept to ensure access to publications in these cases.

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Realization of the bwSync&Share service in Baden-Württemberg - bwSync&Share(-Betrieb)

Contact: Klaus Scheibenberger
Funding: MWK

The state service bwSync&Share is an online storage service for employees and students of universities and colleges in Baden-Württemberg.

CollabFuL - Secure Social Collaboration in Research and Teaching

Contact: Prof. Dr. Hannes Hartenstein
Funding: MWK-BW (IQF)
since 2014-01-01 - 2016-12-31

The CollabFuL: Secure Social Collaboration in Research and Education project aims to create an open, unified, flexible, and privacy-friendly environment for secure social academic information sharing ...

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bwFDM-Communities

since 2014-01-01 - 2015-06-30
Project page: bwfdm.scc.kit.edu

In the long term, the aim is to create added value for researchers by improving the collection, securing, analysis and general availability and searchability of data. As a positive side effect, scientists from Baden-Württemberg will then also be able to assert themselves more easily in research funding decisions by the EU and DFG, because these strongly desire and support the transfer of knowledge even beyond state borders. (Translated with www.DeepL.com)

bwDataArchiv - long-time scientific data storage from research institutions and libraries - bwda

Contact: Jos van Wezel
Funding: MWK
since 2014-01-01 - 2016-12-31
Project page: www.rda.kit.edu

In the scope of the project SCC will become the main archive location in Baden-Württemberg. SCC will further expand its technical infrastructure for the long-time scientific data storage from research institutions and libraries.

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ASTOR - Arthropod Structure revealed by ultrafast Tomography and Online Reconstruction

Contact: Dr. Matthias Bonn
Funding: BMBF
since 2013-11-01 - 2016-06-30
Project page: anka-astor-portal.anka.kit.edu

As part of the ASTOR project, the SCC is developing an online portal based on cloud technologies. Via this portal, users can flexibly use OpenGL-based analysis applications provided via virtual machines for their investigations, regardless of location. (Translated with DeepL.com)

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RADAR - Research Data Repository

Contact: Prof. Dr. Bernhard Neumair
Funding: DFG
since 2013-09-01 - 2016-08-31
Project page: www.radar-service.eu

In the RADAR project, a corresponding service is being set up that primarily offers researchers, institutions and publishers an infrastructure for archiving and publishing research data.

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intelligent Zero Emission Urban System – iZEUS

Contact: Prof. Dr. Hannes Hartenstein
Funding: BMWI
since 2012-01-01 - 2014-06-30

iZeus (intelligent Zero Emission Urban System) is the follow-up project of the research project MeRegioMobil. Its goal is to spur the aspects of SmartGrids and SmartTraffic in the light of the growing importance of electromobility in Germany and Europe with the help of academic research and realistic field tests

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