Welcome to TU Wien Research Data

TU Wien Research Data is an institutional repository of TU Wien to enable storing, sharing and publishing of digital objects, in particular research data. It facilitates the funders' requirements for open access to research data and the FAIR principles by making research output findable, accessible, interoperable and re-usable. It is developed by the TU Wien Center for Research Data Management and hosted by Campus IT.

The repository uses persistent identifiers and synchronises with data hubs: DataCite, OpenAIRE, and BASE. Thus, it maximizes the visibility of the uploaded content. TU Wien Research Data is also listed in FAIRsharing and re3data - registries many funders refer to.

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Deposit research outputs openly, restricted or closed. A landing page provides information on your digital objects, download links, license and persistent identifier.

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Search datasets published by other users.

For any questions regarding this service, please refer to our FAQ and our Upload Guide.

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To get in touch with our team, please visit our 'Contact' page.

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Recent Uploads

Data for "Two-particle calculations with quantics tensor trains -- solving the parquet equations"

Rohshap, Stefan ; Ritter, Marc K. ; Shinaoka, Hiroshi ; von Delft, Jan ; Wallerberger, Markus ; Kauch, Anna Katarzyna

2025-03-13 Dataset Open

This data repository contains the original figures, numerical (raw) data and plot scripts to reproduce the figures from the publication "Two-particle calculations with quantics tensor trains -- solving the parquet equations" at Physical Review Research. The preprint is available on arXiv....

Uploaded on March 14, 2025

Dataset supporting publication: "Remote-sensing based control of 3D magnetic fields using machine learning for in-operando applications".

Cascales Sandoval, Miguel Angel

2025-03-10 (1.0.0) Dataset Open

About the dataset This dataset supports a study where precise 3D magnetic field control is achieved using a hexapole electromagnet system combined with a multi-layer perceptron neural network. The work demonstrates how the neural network enables to calibrate non-linear field responses when...

Physical sciences

Uploaded on March 13, 2025

Der Engel mit dem Lorbeerkranz von der Tambourkuppel der Wiener Karlskirche

Tupy, Anna-Maria ; Krist, Univ. -Prof. Mag. Dr. Gabriela ; Milchin, Univ.-Ass- Mag. art Marija ; Bayerová, Dr. Tatjana ; Zhenzhen, Ma ; University of Applied Arts Vienna

2025-03-12 Report Restricted

Vordiplom von Anna-Maria Tupy an der Universität für angewandte Kunst Wien, Institut für Konservierung und Restaurierung bei o. Univ.-Prof. Mag. Dr. Gabriela Krist und Univ.-Ass. Mag. art Marija Milchin Fach: Konservierung-Restaurierung Wien, am 15. Februar 2016 Die vorliegende Arbeit behandelt...

Karlskirche

Uploaded on March 12, 2025

Elements of Geodetic and Astrometric Very Long Baseline Interferometry

Nothnagel, Axel Gerhard

2025-01-03 (4.2) Text Open

This text is an open tutorial document for educational purposes, e.g., for newcomers to geodetic and astrometric Very Long Baseline Interferometry (VLBI) but also for the specialists wanting to expand their knowledge about topics which are not in their main focus. It is supposed to be a living...

Uploaded on March 10, 2025

Code and training dataset for the publication entitled: "A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications"

Hashemzadeh, Hadi ; Shojaeilangari, Seyedehsamaneh ; Allahverdi, Abdollah ; Rothbauer, Mario ; Ertl, Peter ; Naderi-Manesh, Hossein

2025-02-27 (1.0.0) Dataset Open

Experiment Data & Analysis Overview This repository contains raw data, code and analysis scripts related to experiments performed in the ‘A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications’. The data, code,...

Biological sciences

Uploaded on March 7, 2025