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.
Communities in OPARA
Select a community to browse its collections.
Recent Submissions
OpenBridgeLAB Output-Only Acceleration Data - Reference State, Damage State 1, and Damage State 2
(Technische Universität Dresden, 2026-08-28) Moeller, Max; Juler, Tobias; Patzelt, Adrian; Lenzen, Armin
The OpenBridgeLAB, a testing bridge erected to investigate structural health monitoring methods, was equipped with 32 uniaxial piezoelectric acceleration sensors to measure the structural response under ambient excitation. The bridge is a prestressed concrete bridge consisting of three spans, each with a length of 15 m. The bridge deck comprises three prefabricated T-beam elements. For the investigations, only Spans 1 and 2 were equipped with accelerometers, as Span 3 is structurally decoupled.
The dataset consists of three different ensembles: the Reference State (RS), in which the bridge is in an undamaged condition, Damage State 1 (DS1), and Damage State 2 (DS2). Following the acquisition of the RS measurements, damage was introduced in Span 2 of the OpenBridgeLAB. A second damage was subsequently introduced in Span 1 after the measurements for DS1 had been captured. A detailed description of the damage scenarios and their locations is provided in the companion paper.
In addition to the dataset, a datasheet is provided. The datasheet contains a detailed description of the measurements, including the sensor positions, sampling rate, number of measurements, and data structure.
This research is part of the SPP100+ Priority Programme funded by the German Research Foundation.
Development and Evaluation of a Virtual Reality Environment for Geometry Education: A Design-Based Research Study
(Technische Universität Dresden, 2026-08-28) Josupeit, Judith; Arlt, Annika; Greiß, Annika; Dyrna, Jonathan; Köhler, Thomas
Virtual reality (VR) offers new possibilities for geometry education by enabling learners to explore three-dimensional objects in spatially coherent environments. Despite these benefits, curriculum-related and theory-informed VR learning environments for lower secondary geometry remain limited, especially regarding formative evidence on users’ perceptions and design-related refinement needs. Thus, this study presents the development and formative evaluation of a VR learning environment for lower secondary geometry education, using a design-based research approach. In the environment, learners explored a virtual house and solved geometry tasks related to the geometric properties of the building and its surroundings. The evaluation comprised two phases with 48 participants in total. Quantitative questionnaire data and qualitative feedback were analyzed to examine perceived usability, cybersickness, cognitive load, motivation, perceived learning, didactic suitability, and design-related refinement needs. Overall, participants evaluated the environment positively. Ratings indicated low cybersickness, favorable perceived ease of use, low extraneous cognitive load, high learning-relevant effort, and high intrinsic motivation. Qualitative feedback showed that participants valued spatial exploration and perspective-taking, but also identified needs for more interaction, improved documentation of intermediate results, integrated feedback, and feasible classroom implementation.
FedSurg EndoVis 2024: Challenge Subset of Appendix300
(Technische Universität Dresden, 2026-08-27) Kirchner, Max; Kolbinger, Fiona R; Jenke, Alexander C; Saldanha, Oliver L; Pfeiffer, Kevin; Kanjo, Weam; Kather, Jakob N.; Bodenstedt, Sebastian; Speidel, Stefanie
This deposit contains the supplementary data for the FedSurg EndoVis 2024 Challenge, the first federated learning challenge in Surgical Data Science, held at MICCAI 2024.
The challenge used a preliminary subset of the Appendix300 dataset, a multi-institutional collection of laparoscopic appendectomy recordings from German university and community hospitals, annotated with intraoperative appendicitis severity grades 0 to 5 following Gomes et al. The challenge cohort comprises 223 recordings across four centers, split into 153 training and 70 test cases.
The deposit includes a CSV file specifying which Appendix300 samples were used in the challenge and their assignment to centers and to the training and test splits, together with two recordings that were used in the challenge but excluded from the final Appendix300 dataset because the available footage was shorter than the nominal 100 second window or the appendix was not clearly visible at the annotated timestamp.
This deposit does not contain the appendectomy video recordings themselves, with the exception of the two excluded cases named above. The video data and accompanying clinical metadata are available separately as the Appendix300 dataset at https://doi.org/10.25532/OPARA-1173. The challenge evaluation and ranking code is available at https://gitlab.com/nct_tso_public/challenges/miccai2024/snippet, and the example federated learning setup at https://gitlab.com/nct_tso_public/challenges/miccai2024/FedSurg24.
Use of this material requires citation of both the FedSurg challenge paper and the Appendix300 data descriptor. Released under CC BY.
Data Sets for Paper "A Leaner and Faster Web: How CBOR Can Improve Dynamic Content Encoding in JSON and DNS over HTTPS"
(Technische Universität Dresden, 2026-08-27) Lenders, Martine S.; Bormann, Carsten; Schmidt, Thomas C.; Wählisch, Matthias
These data sets contain the files to recreate our evaluations using the code archived at https://doi.org/10.5281/zenodo.21790597. This is a supplement to the paper
- M. S. Lenders, C. Bormann, T.C. Schmidt, and M. Wählisch, “**A Leaner and Faster Web: How CBOR Can Improve Dynamic Content Encoding in JSON and DNS over HTTPS**,” IEEE Transactions on Network and Service Management (TNSM), August 2026. https://doi.org/10.1109/TNSM.2026.3722114
**Paper abstract:** The Internet community has taken major efforts to decrease latency on the World Wide Web with significant improvements in accelerating content transport and in compressing static content. Less attention, however, has been dedicated to compression of dynamic content. Such content is commonly provided by JSON and DNS over HTTPS. Dynamic content objects continue to grow in size, which increases latency and fosters the digital inequality. In this paper, we propose to mitigate this increase by utilizing Concise Binary Object Representation (CBOR), a standard originally designed for the constrained Internet of Things (IoT) to restrict packet sizes and enable efficient encoding of data objects. We provide protocol design and three new data sets for the evaluation of dynamic content, DNS, and the loading of websites. Our key findings are the following: _(i)_ Switching the data representation from JSON to CBOR reduces data by up to 80%. This size reduction can decrease loading times by up to 13.8% when downloading large objects—even in local setups. _(ii)_ Enabling CBOR for DNS over HTTPS (DoH) and DNS over CoAP (DoC) reduces packet sizes significantly. Compressing only names combined with unpacked CBOR achieves maximum gain of 52.2%, using more complex but still lightweight Packed CBOR allows minimizing packets by up to 95.5%. Our lean decoder for name compression can fit into as little as 314 bytes of build size. Our results clearly show the potential of CBOR outside of IoT scenarios. Parts of this research have already influenced work within the IETF.
Mobilität in Städten – SrV 2018
(Technische Universität Dresden, 2026-08-26) Hubrich, Stefan; Ließke, Frank; Wittwer, Rico; Wittig, Sebastian; Gerike, Regine
Im SrV 2018 wurden insgesamt 186.832 Personen in 83.318 Haushalten befragt. Dabei wurden 622.582 Wege erfasst. Die Befragungen fanden in 135 deutschen Städten und Gemeinden, verteilt auf 118 Untersuchungsräume statt. Für die wissenschaftliche Nutzung werden a) stadtübergreifende Datensätze für verschiedene Stadtgruppen sowie b) stadtspezifische Datensätze für einzelne Städte bzw. Untersuchungsräume bereitgestellt. Einen Überblick über verfügbare Städte, Untersuchungsräume und Stadtgruppen bietet die Webseite zum SrV 2018: https://tu-dresden.de/srv/srv-2018. Die Daten stehen in den Dateiformaten CSV (Comma-Separated Values), ACCDB (Microsoft Access) sowie SAV (SPSS) zur Verfügung. Die Datensätze gliedern sich jeweils in eine Haushalts-, eine Personen- und eine Wegeebene. Die Datenbereitstellung erfolgt über die Professur für Mobilitätssystemplanung: https://tu-dresden.de/srv/das-srv/wissenschaftliche-nutzung. Vor der Bereitstellung wird eine Nutzungsvereinbarung geschlossen. Stadtübergreifende Datensätze (a) können direkt angefordert werden. Stadtspezifische Datensätze (b) sind nach Freigabe durch die jeweiligen auftraggebenden Institutionen nutzbar. Die Professur für Mobilitätssystemplanung stellt in diesen Fällen den Kontakt zu den relevanten Institutionen her. Darüber hinaus stehen stadtübergreifende Auswertungen für Stadtgruppen (Tabellenberichte und Mobilitätssteckbriefe) sowie der SrV-Städtevergleich auf der Webseite des SrV 2018 zum Download bereit: https://tu-dresden.de/srv/srv-2018. Stadtspezifische Auswertungen sind analog zu den stadtspezifischen Datensätzen nach Freigabe durch die jeweiligen auftraggebenden Institutionen verfügbar.
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A total of 186,832 individuals from 83,318 households took part in the SrV 2018 survey, and information on 622,582 trips was collected. The survey was conducted in 135 cities and municipalities across Germany, grouped into 118 study areas. The following datasets are available for scientific use: a) cross-city datasets for different city groups and b) city-specific datasets for individual cities or study areas. The SrV 2018 website provides an overview of the available cities, study areas, and city groups: https://tu-dresden.de/srv/srv-2018. The data are available in CSV (Comma-Separated Values), ACCDB (Microsoft Access), and SAV (SPSS) file formats. Each dataset is organized into household-, person-, and trip-level data. The datasets are made available through the Chair of Mobility System Planning: https://tu-dresden.de/bu/verkehr/ivs/srv/das-srv/wissenschaftliche-nutzung. A data use agreement must be signed before the data are made available. Cross-city datasets (a) can be requested directly. City-specific datasets (b) are available subject to approval by the respective commissioning institutions. In such cases, the Chair of Mobility System Planning will facilitate contact with the relevant institutions. In addition, cross-city reports for city groups (tabular reports and mobility fact sheets) as well as the SrV City Comparison are available for download on the SrV 2018 website: https://tu-dresden.de/srv/srv-2018. City-specific reports, like the corresponding city-specific datasets, are available subject to approval by the respective commissioning institutions.