Collaborative Research Center/Transregio 280: “Design Strategies for Material-Minimized Carbon-Reinforced Concrete Structures – Principles of a New Approach to Construction” - Information infrastructure Project
Reproducibility of research and the application of FAIR (Findable, Accessible, Interoperable, Reusable) data principles are essential elements of good scientific practice and rely on effective research data and information management. During the first funding period of TRR 280, the service project INF established an integrated data and information infrastructure for the entire consortium and supported researchers in its use. Based on a comprehensive requirements analysis conducted in close collaboration with all projects, the infrastructure was tailored to manage and process diverse data types, including numerical, simulation, mechanical, and computer tomography data. Particular emphasis was placed on best practices across the data life cycle, including structured data storage, consistent metadata annotation, and making research data accessible and searchable.
In the second funding period, INF focuses on extending and professionalizing the existing infrastructure. In close cooperation with the Service Center Research Data of TU Dresden, dedicated workshops were conducted to systematically collect evolving data management requirements, harmonize metadata understanding, and design standardized data workflows and automations. From phase two onwards, a licensed research data management platform (Mediaflux) is used as the backend system. Within this framework, metadata schemas for common data types are being developed and implemented, and new data models, workflows, and requirements from newly integrated research projects are incorporated into the infrastructure.
Across both funding periods, INF operates the central research data infrastructure, provides continuous support and training in research data management and associated tools, and further adapts the system to the needs of the researchers. Ongoing activities include monitoring and integrating relevant services from the German National Research Data Initiative (NFDI), particularly NFDI4Ing, as well as supporting the use of high-performance computing resources. In addition, INF assists research projects in applying artificial intelligence and machine learning methods for data analysis and construction, in collaboration with the national competence center ScaDS.AI Dresden/Leipzig, including requirements analysis, implementation support, and access to suitable HPC resources.
Project website
https://www.sfbtrr280.de/forschung/begleitprojekte/teilprojekt-inf/
Partners
-
Technische Universität Dresden (TUD)
-
RWTH Aachen University
-
Universität Hamburg
-
Leibniz-Institut für Polymerforschung Dresden e. V.
-
Technische Universität Darmstadt
ZIH contact
Project Duration
07/2024–06/2028
Funding
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) ‒ SFB/TRR 280, Project-ID 417002380
