04/21/2026 | Press release | Archived content
Different types of research data entail different challenges for users. Six researchers share their experiences with research data and the implementation of the FAIR principles from a wide range of perspectives.
© TU Wien / Livia Beck
From left: Sabine Sint, Adil Mukhtar, Paweł W. Woźniak, Markus Valtiner, Francesca Mangani, and Gabriel Wurzer
From left: Sabine Sint, Adil Mukhtar, Paweł W. Woźniak, Markus Valtiner, Francesca Mangani, and Gabriel Wurzer
From physics and mechanical engineering to architecture - both qualitative and quantitative research data are generated in almost all scientific disciplines. The FAIR principles ensure that research data is findable, accessible, interoperable, and reusable. In part two of the series "Research data - we care to make it FAIR!" (follow this link to part 1 of the series), we take a look at exactly these areas of application.
© TU Wien / Livia Beck
Sabine Sint
Sabine Sint
Sabine Sint from the Research Unit of Building Physics works at the interface between the planning, simulation, and operation of buildings. In this interview, she talks about the diverse data landscape in her field, building simulations and digital twins, and the importance of documentation for secure, sustainable data sharing.
Read more: https://www.tuwien.at/en/research/rti-support/research-data/news/news/between-construction-plans-and-simulations, opens an external URL in a new window
© TU Wien / Livia Beck
Markus Valtiner
Markus Valtiner
Markus Valtiner is a physicist specialised in data-intensive experiments at interfaces. Imaging techniques such as atomic force microscopy (AFM) and spectroscopic methods such as X-ray photoelectron spectroscopy (XPS) produce large amounts of data that are processed and converted into open, machine-readable structures.
Read more: https://www.tuwien.at/en/research/rti-support/research-data/news/news/surfaces-meet-automated-data-flows, opens an external URL in a new window
© TU Wien / Livia Beck
Adil Mukhtar
Adil Mukhtar
Adil Mukhtar demonstrates how AI is used in building sciences - and where its limitations lie. In the interview, he talks about training models for fault detection in building systems and the intricacies of simulation datasets and explainable AI methods. The conversation also touches on the contrasting research cultures in building physics and computer science and their significance for data sharing.
Read more: https://www.tuwien.at/en/research/rti-support/research-data/news/news/from-black-box-to-reproducible-ai-model, opens an external URL in a new window
© TU Wien / Livia Beck
Gabriel Wurzer
Gabriel Wurzer
Gabriel Wurzer focuses on data in the context of architecture and planning. His contribution makes it clear that data only reveals its value when placed within a specific application context, such as in simulations or Building Information Models (BIM). Wurzer is convinced that creative work will remain the preserve of humans, whilst AI can take over routine tasks.
Read more: https://www.tuwien.at/en/research/rti-support/research-data/news/news/data-is-nothing-without-purpose, opens an external URL in a new window
© TU Wien / Livia Beck
Paweł W. Woźniak
Paweł W. Woźniak
Paweł W. Woźniak from the Research Unit of Human Computer Interaction reports on his experiences with technology acceptance, diverse user research methods, the handling of qualitative data, and user-centred prototype design. Qualitative data, as generated in the field of prototype research, is often difficult to reproduce and consequently harder to align with the FAIR principles.
Read more: https://www.tuwien.at/en/research/rti-support/research-data/news/news/ai-on-the-rise-new-opportunities-for-hci, opens an external URL in a new window
© TU Wien / Livia Beck
Francesca Mangani
Francesca Mangani
Francesca Mangani is an aeronautical engineer specialised in turbulent multiphase flows. Her simulations of drop distributions are run on modern high-performance computers, which speed up the calculations many times over. As sharing raw data would, on the one hand, overload networks and, on the other, be of no use to colleagues without access to supercomputers, she publishes code as open source instead.
Read more: https://www.tuwien.at/en/research/rti-support/research-data/news/news/drops-bubbles-and-supercomputing, opens an external URL in a new window
With the TU Wien Research Data, opens an external URL in a new window repository, TU Wien provides a suitable and certified platform for implementing the FAIR principles. Researchers at TU Wien are invited to actively use the repository and to contact the research data team with any questions.
Contact:research.data@tuwien.ac.at
Website: http://www.tuwien.at/en/researchdata