Research Data Repository of Saxon Universities

OPARA is the Open Access Repository and Archive for Research Data of Saxon Universities.


Researchers of Saxon Universities can either publish their research data on OPARA, or archive it here to comply with requirements of funding acencies and good scientic practice, without public access.

You can find the documentation of this service at the ZIH Data Compendium websites. If you need suppourt using OPARA please contact the Servicedesk of TU Dresden.

Please note: The OPARA service was recently upgraded to a new technical platform (this site). Previously stored data will not be available here immediately. It can be found at the still active old version of OPARA. These stock data will be migrated in near future and then the old version of OPARA will finally be shut down. Existing DOIs for data publications remain valid.

Artwork based on 1, 2, 3, 4  @pixabay
 

Recent Submissions

Item
Open Access
Predictive maintenance demonstrator dataset with individual load histories
(Technische Universität Dresden, 2025-04-14) Heindel, Leonhard; Hantschke, Peter; Kästner, Markus
Predictive maintenance aims to develop methods that are capable of predicting component failure before it occurs. Virtual sensing methods predict unmeasured physical quantities from available measurement data. These methods offer significant benefits to predictive maintenance, since virtual sensors can be used to estimate quantities that are difficult to measure. In many real applications, the time to failure is in the range of years, complicating the development and validation of predictive maintenance and virtual sensing approaches. This dataset provides a demonstrator example where failure occurs based on individual load histories. The sensor setup consists of simple notched steel specimens, which are clamped between two servo-hydraulic cylinders of a fatigue test bench. It is designed to provide a virtual sensor use case with independent training and testing data, so that the dataset can be used for algorithm development and benchmarking purposes.
Item
Open Access
Data corresponding to the publication: "SU(N) altermagnetism: Lattice models, magnon modes, and flavor-split bands" by P. M. Cônsoli and M. Vojta (2025)
(Technische Universität Dresden, 2025-04-11) Monteiro Consoli, Pedro; Vojta, Matthias
This dataset contains the scripts that generated the data and figures from the preprint P. M. Cônsoli and M. Vojta, "SU(N) altermagnetism: Lattice models, magnon modes, and flavor-split bands", arXiv:2402.18629, which has been accepted for publication in Physical Review Letters.
Item
Open Access
BiSID-5k: A Bimodal Image Dataset for Seed Classification from the Visible and Near-Infrared Spectrum
(Universität Leipzig, 2025-04-10) Kukushkin, Maksim; Bogdan, Martin; Goertz, Simon; Callsen, Jan-Ole; Oldenburg, Eric; Enders, Matthias; Schmid, Thomas
The success of deep learning in image classification has been largely underpinned by large-scale datasets, such as ImageNet, which have significantly advanced multi-class classification for RGB and grayscale images. However, datasets that capture spectral information beyond the visible spectrum remain scarce, despite their high potential, especially in agriculture, medicine, and remote sensing. To address this gap in the agricultural domain, we present BiSID-5k, a thoroughly curated bimodal seed image dataset comprising paired RGB and hyperspectral images for 10 plant species, making it one of the largest bimodal seed datasets available. We describe the methodology for data collection and preprocessing and benchmark several deep learning models on the dataset to evaluate their multi-class classification performance. By contributing a high-quality dataset, BiSID-5k offers a valuable resource for studying spectral, spatial, and morphological properties of seeds, opening new avenues for research and applications.
Item
Open Access
Earthquakes in Saxony (Germany) and surroundings from 2006 up to 2023 -- onsets and locations
(Universität Leipzig, 2025-04-04) Wendt, Siegfried
This archive contains complete results of earthquake locations for Saxony (Germany) and neighbourhood of the years from 2006 up to 2023. Approximately 26.000 events were detected and localized, most of them with epicenters in Northwestern Bohemia near Nový Kostel and Luby (Czech Republic) neighboured to the Saxon border.
Item
Open Access
Data corresponding to the publication "Optical and acoustic plasmons in the layered material Sr2RuO4"
(Technische Universität Dresden, 2025-03-21) Schultz, Johannes; Lubk, Axel; Jerzembeck, Fabian; Kikugawa, Naoki; Knupfer, Martin; Wolf, Daniel; Büchner, Bernd; Fink, Jörg
We use momentum-dependent electron energy-loss spectroscopy in transmission to study collective charge excitations in the layer metal Sr2RuO4. This metal has a transition from a perfect Fermi liquid below T~30 K into a "strange" metal phase above T~800 K. We cover a complete range between in-phase and out-of-phase oscillations. Outside the classical range of electron-hole excitations, leading to a Landau damping, we observe well-defined plasmons. The optical (acoustic) plasmon due to an in-phase (out-of-phase) charge oscillation of neighbouring layers exhibits a quadratic (linear) positive dispersion. Using a model for the Coulomb interaction of the charges in a layered system, it is possible to describe the range of optical plasmon excitations at high energies in a mean-field random phase approximation without taking correlation effects into account. In contrast, resonant inelastic X-ray scattering data show at low energies an enhancement of the acoustic plasmon velocity due to correlation effects. This difference can be explained by an energy dependent effective mass which changes from ~ 3.5 at low energy to 1 at high energy near the optical plasmon energy. There are no signs of over-damped plasmons predicted by holographic theories.