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 OPARA manual websites. If you need suppourt using OPARA please contact the Servicedesk of TU Dresden.

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

Communities in OPARA

Select a community to browse its collections.

Recent Submissions

ItemOpen Access
Quellcode und Datenmodell der Forschungsdatenbank Schwingfestigkeitsversuche für Wellen und Welle-Nabe-Verbindungen
(Technische Universität Dresden, 2026-10-23) Becker, Nils
Der vorliegende Datensatz beinhaltet den Quellcode der Datenbankanwendung (Quellcode.zip), das zugehörige Datenmodell in unterschiedlichen Formaten und ein Backup der Datenbank mit vorliegenden Daten aus mehreren Forschungsprojekten zum Stand Februar 2026. Der Quellcode kann zum Aufsetzen der Datenbankanwendung genutzt werden, anschließend kann das Backup der Datenbank bei Bedarf eingespielt werden.
ItemOpen Access
An Annotated Multi-Platform Laser Scanning Dataset (MLS, ULS, TLS) for Semantic Segmentation of Point Clouds in Complex Forest Environments
(Technische Universität Dresden, 2026-10-20) Matzke, Felix Rocco; Eltner, Anette
Available datasets for semantic segmentation of forest point clouds mostly contain data from a single sensing system. This dataset provides LiDAR point clouds of a forest scene in the Richterschlüchte area, Saxon Switzerland, Germany, acquired during a field campaign in March 2023 using three different laser scanning systems: mobile laser scanning (MLS), uncrewed aerial vehicle laser scanning (ULS), and terrestrial laser scanning (TLS). All point clouds were manually annotated with three semantic classes, namely trunk, ground, and miscellaneous. In total, five point clouds are included: the MLS point cloud is partitioned into training, validation, and test subsets, while the TLS and ULS point clouds are provided to assess generalization across varying sensing systems. The dataset is intended for developing and testing deep learning approaches for the semantic segmentation of point clouds in complex forest environments.
ItemOpen Access
Research data for stakeholders and their strategic interaction in Germany’s energy transition
(Technische Universität Bergakademie Freiberg, 2026-10-20) Li, Anqi; Brumme, Anja; Rübbelke, Dirk
This dataset provides the materials underlying the systematic literature review and cross-impact balance (CIB) analysis of stakeholder interactions in Germany’s energy transition. It includes the literature search strategies, the list and descriptive analysis of the 95 included studies, the study coding and strategy state descriptions, the CIB matrix with scoring rationales and supporting references, and the ScenarioWizard model file.
ItemOpen Access
Data corresponding to publication: “Emergent relativistic symmetry from interacting fermions on the honeycomb bilayer” by Z. H. Liu and L. Janssen (2026)
(Technische Universität Dresden, 2026-10-16) Liu, Zihong
This dataset contains numerical data and analysis scripts associated with the publication Z. H. Liu and L. Janssen, “Emergent relativistic symmetry from interacting fermions on the honeycomb bilayer”, Physical Review B (2026), and its Supplemental Material. It includes charge-density-wave correlations, quasiparticle observables, finite-temperature charge susceptibility, single-particle spectra, and finite-size scaling and crossover analyses. The compressed archive preserves the original directory structure, including intermediate results and alternative analyses, and includes a README describing the contents and data formats, together with file checksums.
ItemOpen Access
High-contrast mineral-bonded composite systems for impact protection (GRK 2250, Project A6 II)
(Technische Universität Dresden, 2026-10-16) Leicht, Lena
The presented data belongs to reinforced concrete (RC) cuboid experiments in the drop tower of TU Dresden. The experiments aimed at characterizing different mineral-bonded composite systems regarding their impact protection performance. Different sensors, such as accelerometers, a laser Doppler vibrometer (LDV), and two high-speed cameras (HSC) tracked the specimen behavior during the experiments. The data is the calibrated and filtered data of these sensors with different evaluations carried out and stored in the files corresponding to the individual experiments.