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.
Communities in OPARA
Select a community to browse its collections.
Recent Submissions
Item
Open Access
Research Data Management Handbook for SPP100+
(Technische Universität Dresden, 2025-06-27) Aqlan , Samar; Kang, Chongjie; Eisermann, Cedric
This handbook provides a comprehensive guide to research data management (RDM) for the joint project SPP100+, an interdisciplinary initiative that brings together five research clusters and approximately 19 subprojects. The project addresses the urgent need for earlier and more effective preventive maintenance of complex structural systems—such as those found in transport infrastructure—by enabling predictive insights into degradation processes. As structures age, their condition deteriorates increasingly rapidly, making early detection and intervention crucial. SPP100+ focuses on advancing the collection, integration, and evaluation of data related to geometry, material properties, stress, and ageing. Central to this effort is the concept of the digital twin, which allows for real-time, data-driven decision-making in the maintenance and operation of unique, large-scale infrastructure. This handbook outlines the RDM strategies tailored to the project's unique demands, supporting consistent, interoperable, and reusable data practices across all contributing research units.
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Open Access
Data Underpinning: Spin Liquid Mimicry in the Hydroxide Double Perovskite CuSn(OD)₆ Induced by Correlated Proton Disorder
(Technische Universität Dresden, 2025-06-26) Kulbakov, Anton A.; Häußler, Ellen; Parui, Kaushick K.; Pavlovskii, Nikolai S.; Mannathanath Chakkingal, Aswathi; Granovsky, Sergey A.; Gaß, Sebastian; Corredor Bohórquez, Laura Teresa; Wolter, Anja U. B.; Zvyagin, Sergei A.; Skourski, Yurii V.; Pomjakushin, Vladimir Yu.; Puente-Orench, Inés; Peets, Darren Campbell; Doert, Thomas; Inosov, Dmytro. S.
The face-centered-cubic lattice is composed of edge-sharing tetrahedra, making it a leading candidate host for strongly frustrated magnetism, but relatively few face-centered frustrated materials have been investigated. In the hydroxide double perovskite CuSn(OH)6, magnetic frustration of the Cu2+ quantum spins is partially relieved by strong Jahn-Teller distortions. Nevertheless, the system shows no signs of long-range magnetic order down to 45 mK and instead exhibits broad thermodynamic anomalies in specific heat and magnetization, indicating short-range dynamical spin correlations — a behavior typical of quantum spin liquids. We propose that such an unusual robustness of the spin-liquid-like state is a combined effect of quantum fluctuations of the quantum spins S = 1/2 , residual frustration on the highly distorted face-centered Cu2+ sublattice, and correlated proton disorder. Similar to the disorder-induced spin-liquid mimicry in YbMgGaO4 and herbertsmithite, proton disorder destabilizes the long-range magnetic order by introducing randomness into the magnetic exchange interaction network. However, unlike the quenched substitutional disorder on the magnetic sublattice, which is difficult to control, proton disorder can in principle be tuned through pressure-driven proton ordering transitions. This opens up the prospect of tuning the degree of disorder in a magnetic system to better understand its influence on the magnetic ground state.
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Open Access
eBike measurements for fatigue monitoring using acceleration differences
(Technische Universität Dresden, 2025-06-26) Heindel, Leonhard; Hantschke, Peter; Kästner, Markus
In fatigue monitoring, the aim is to approximate the fatigue damage accumulation in a system, for example to schedule maintenance intelligently. Virtual sensing can be deployed to obtain the required information more efficiently by estimating them from readily available sensor data. This dataset contains acceleration and strain measurements from a sensor equipped eBike, designed to develop such methods. Using the acceleration data, the aim is to estimate the fatigue damage accumulation at the strain gauge positions. Here, the sensors are positioned such that differences between multiple acceleration sensors provide information that is related to the deformation of the eBike frame, so that a connection to strain gauge data can be established by computing differences between integrated displacement data. The dataset includes data intended for training and testing of data-driven modeling approaches, which is obtained from regular eBike usage. Additional labeled data enables the analysis of specific riding maneuvers.
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Open Access
Forschungsdaten zur Dissertation: Konzeption eines fachdidaktischen Patternmodells für den Informatikunterricht
(Universität Leipzig, 2025-06-19) Kießling, Peter
Diese Datenpublikation umfasst die im Rahmen der Dissertation „Konzeption eines fachdidaktischen Patternmodells des Informatikunterrichts in den Dimensionen Inhalt, Methode und Medium“ (Kießling, 2025, Universität Leipzig) erhobenen Forschungsdaten. Enthalten sind anonymisierte Daten der Vorstudie (Phasen I und II), der Hauptstudie sowie der explorativen Wirksamkeitsanalyse. Darüber hinaus beinhaltet die Publikation eine Demoversion des im Forschungsprozess entwickelten IML-Modells.
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Open Access
MiTra: A Drone-Based Trajectory Data for an All-Traffic-State Inclusive Freeway with Ramps
(Technische Universität Dresden, 2025-06-13) Chaudhari, Ankit Anil; Treiber, Martin; Okhrin, Ostap
This dataset contains original videos, tracking logs to validate the videos, and extracted trajectory data of naturalistic traffic collected using unmanned aerial vehicles (drones) over a 900 m section of the A50 urban freeway in Milan, Italy. Nine flight campaigns, totaling 135 min, were conducted using six drones flying in a line to capture comprehensive coverage across all traffic states, from free flow to congested conditions.
The dataset offers detailed trajectory data extracted from single drone videos (54 datasets from nine flight campaigns of six drones) and 9 datasets of stitched footage from all six drones. With a granularity of 30 frames per second, we extracted 124,641 vehicle trajectories from single drone videos and 24,161 trajectories from stitched footage. This enables complete vehicle tracking across five distinct categories: Cars (73.0%), Medium Vehicles (13.4%), Heavy Vehicles (11.3%), Motorcycles (2.1%), and Buses (0.2%).
Of the total vehicles, 76.9% traveled straight on the freeway, while 13% merged and 10.1% diverged using on-ramps and off-ramps, respectively, in both directions. Regarding lane changes, 51.9% of the vehicles in the dataset executed at least one. Among these, 24.8% performed a single lane change, while 27.1% changed lanes multiple times.
In addition to trajectory data, this dataset includes the original videos and tracking files, which show the recorded traffic scenes, provide visual context, and enhance the usability and interpretability of the trajectory data. The tracking files can be used to map vehicle IDs in the video, enabling various analyses as detailed in the user guide.
This dataset facilitates the analysis of driving behavior, traffic dynamics, and vehicle interactions, offering valuable insights for research, planning, and policymaking in transportation and urban mobility.