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
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.
Mobilität in Städten – SrV 2013
(Technische Universität Dresden, 2026-08-26) Ahrens, Gerd-Axel; Ließke, Frank; Wittwer, Rico; Hubrich, Stefan; Wittig, Sebastian
Im SrV 2013 wurden insgesamt 123.098 Personen in 51.987 Haushalten befragt. Dabei wurden 394.406 Wege erfasst. Die Befragungen fanden in etwa 300 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 2013: https://tu-dresden.de/srv/archiv/srv-2013. 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 2013 zum Download bereit: https://tu-dresden.de/srv/archiv/srv-2013. Stadtspezifische Auswertungen sind analog zu den stadtspezifischen Datensätzen nach Freigabe durch die jeweils auftraggebenden Institutionen verfügbar.
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A total of 123,098 individuals from 51,987 households took part in the SrV 2013 survey, and information on 394,406 trips was collected. The survey was conducted in approximately 300 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 2013 website provides an overview of the available cities, study areas, and city groups: https://tu-dresden.de/srv/archiv/srv-2013. 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 2013 website: https://tu-dresden.de/srv/archiv/srv-2013. City-specific reports, like the corresponding city-specific datasets, are available subject to approval by the respective commissioning institutions.
Mean Stress Sensitivity of Cold-Worked High-Purity Copper: A comprehensive dataset
(Technische Universität Dresden, 2026-08-25) Schneider, Tom; Schöne, Sebastian; Bohot, André; Lauf, Matthias; Werdin, Sven; Hantschke, Peter; Zimmermann, Martina; Kästner, Markus
The influence of work hardening on the fatigue behaviour of high-purity copper was investigated using commercially available sheet material (3 mm thickness, as-delivered, no additional rolling or heat treatment) in three strength classes (indicated by their R-number, a measure of minimum tensile strength): R240 (two independently supplied batches, R240-1 and R240-2), R290, and R360. These material states are representative of copper conductors used in electrical applications such as traction motors, generators, and battery systems.
For each material state, the dataset comprises:
1. Microstructural characterization by electron backscatter diffraction (EBSD).
2. Quasi-static (monotonic) tensile tests in strain control, using the same specimen geometry as the fatigue specimens (10 mm gauge length; not a standard tensile geometry, so results beyond necking are not comparable to standardized tensile tests).
3. Load-controlled fatigue (Wöhler/S-N) tests on smooth, unnotched specimens at several load ratios, used to quantify the combined effect of mean stress and work-hardening state on fatigue strength. Run-out was defined at 5 10^7 load cycles.