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
 

Communities in OPARA

Select a community to browse its collections.

Recent Submissions

Item
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.
Item
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.
Item
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.
Item
Open Access
GHG EMISSION FACTORS OF FUELS
(Technische Universität Dresden, 2025-06-12) Wang, Haibin
According to the data presented IMO’s 4th GHG study and FuelEU Maritime Regulation, the potential emissions generation from the use of different fuels are collected considering the WtT and TtW emissions in terms of GHGIE (g CO2 eq./MJ) from the production, transportation and usage of fuels.
Item
Open Access
Hydrogen fuelled ships: Comparative analysis of class rules and guidelines
(Technische Universität Dresden, 2025-06-12) Injun , Yang
The IGF Code, originally designed around LNG storage and transport systems, falls short in adequately addressing the unique properties of hydrogen. As a result, efforts are currently underway to develop relevant regulations, including the release of CCC 9/WP.3. Leading classification societies like ABS, BV, DNV, KR, LR, NK, and RINA have established their own specific rules and guidelines for liquefied gases and LNG.