Purchase and operation of experiment-specific Tier-2 online storage for ATLAS and CMS at GridKa at KIT.
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.
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.
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.
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.
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.
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’.
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.
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.
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)
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.
The NFDI-MatWerk consortium receives five years of funding as part of the National Research Data Infrastructure (NFDI) for the development of a standardized platform for research data in materials science and engineering. In this specialist area, the physical mechanisms of materials are characterized in order to develop resource-saving materials with ideal properties for the respective applications. Using a knowledge graph-based infrastructure, it should be possible to access research data distributed throughout Germany in such a way that even search queries and evaluations on complex topics can be made quickly and easily accessible. At KIT, the Scientific Computing Center (SCC) and the Institute for Applied Materials (IAM) are involved. At the SCC, we are building the digital research environment with the NFDI-MatWerk partners Translated with DeepL.com (free version)
NEP stands for “Nanoscience Foundries & Fine Analysis Europe Pilot” and is a European infrastructure project. It provides important resources for nanoscience research and develops new cooperative working methods. Comprehensive data management technologies and an open access data archive will make the research data FAIR and ensure interoperability with the European Open Science Cloud. In this project, the SCC is developing innovative tools for research data and metadata management, which are essential components of the NEP infrastructure. The SCC is also responsible for the “Virtual Access” work package. Translated with DeepL.com (free version)
As part of the Joint Lab “Integrated Model and Data Driven Materials Characterization” (MDMC), the Simulation Data Laboratory (SDL) for Materials Science is developing a concept for a data and information platform. This platform is intended to make data on materials available in a knowledge-oriented manner as an experimental basis for digital twins on the one hand and for the development of simulation-based methods for predicting material structure and properties on the other. The platform defines a metadata model for the description of samples and data sets from experimental measurements. In addition, data models for material simulation and correlative characterization are harmonized using materials science vocabularies and ontologies. Translated with DeepL.com (free version)
NFDI4ING is an engineering consortium that promotes the management of technical research data. NFDI4ING was founded 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 research data FAIR - findable, accessible, interoperable and reusable. An important challenge here is the large number of engineering sub-disciplines and their subject-specific characteristics. 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 develops and implements 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)
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)
The overarching goal of the Helmholtz Metadata Collaboration Platform is to promote the qualitative enrichment of research data through metadata in the long term, to support researchers - and to implement this in the Helmholtz Association and beyond. With the FAIR Data Commons Technologies work package, the SCC is developing technologies and processes to make research data from all research areas of the Helmholtz Association available and to provide researchers with easy access in accordance with the FAIR principles. This is achieved on a technical level through standardized interfaces that are based on recommendations and standards developed 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 work. Translated with www.DeepL.com/Translator (free version)
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.
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).
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.
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.
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
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
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 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 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.
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.
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.
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.
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.
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.
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)
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.
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.
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.
EUDAT - the collaborative Pan-European infrastructure providing research data services, training and consultancy for Researchers Research Communities Research Infrastructures & Data Centres
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.
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 ...
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)
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.
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.
