Architectural research faces a key challenge: despite the growing importance of structured research data, there is still a lack of available, standardized, and usable datasets. Heterogeneous sources, unresolved copyright issues, limited data literacy, and complex visual formats such as CAD drawings make publication difficult, resulting in fragmented research data that is rarely shared.

A new project funded by the German Research Foundation (DFG) addresses these obstacles head-on. Building on the NFDI4ING Seed Fund initiative “RDM-Workflows for Construction Engineering and Architecture” Darmstadt University and State Library (ULB) and the Institute for Computational Design and Construction (ICD) at the University of Stuttgart are jointly developing an “Architectural Research Data Management Pipeline”. The user-friendly web application will integrate existing NFDI services and automatically transform research data into linked knowledge graphs, enabling enriched datasets to be published as FAIR Digital Objects.

The project pursues two core objectives:

• More efficient data management: The pipeline will support researchers with clear workflows and templates to systematically capture data, files, and sources, significantly improving the quality of architecture-related research data.
• Practice-oriented development: Close collaboration with the research community and NFDI services will ensure that the pipeline meets real-world needs and can be adopted directly in practice.

Implementation is structured into three work packages: further development of an existing prototype; the creation of a showcase demonstrator based on data from multi-storey timber construction projects; and continuous exchange with the community and infrastructure stakeholders through workshops and conferences.

In the long term, the Architectural Research Data Management Pipeline is intended to become a scalable service that can be applied in other research domains as well. By tightly linking research and infrastructure, the project will deliver a modular workflow that supports data-driven methods, enables FAIR publication, and represents visual data appropriately. In doing so, it will make an important contribution to greater transparency, reproducibility, and quality in architectural research.