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
Multi-Domain Optimization for Networked Control Systems
(Technische Universität Dresden, 2026-04-30) Pallewaththe Kankanamge, Hasal Dinusankha Kulasekara; Soler Perez Olaya, Santiago; Wollschlaeger, Martin
This repository contains the experimental artifacts for our paper on multi-domain model-driven optimization for networked control systems, providing a comprehensive suite of resources for system modeling and evaluation, including:
- plant-side dynamical models,
- communication-delay models,
- neural-network surrogate training and evaluation,
- objective-function analysis for accuracy-versus-computation trade-offs, and
- optional Hailo deployment and latency measurements.
Appendix300: Surgical video and patient metadata of 330 laparoscopic appendectomy cases from five institutions
(Technische Universität Dresden, 2026-04-29) Kolbinger, Fiona R; Kirchner, Max; Pfeiffer, Kevin; Bodenstedt, Sebastian; Jenke, Alexander C; Barthel, Julia; Carstens, Matthias; Dehlke, Karolin; Dietz, Sophia; Emmanouilidis, Sotirios; Fitze, Guido; Freitag, Martin; Holderried, Fabian; Jacobi, Thorsten; Kanjo, Weam; Leitermann, Linda; Mees, Sören Torge; Pistorius, Steffen; Prudlo, Conrad; Seiberth, Astrid; Schultz, Jurek; Thiel, Karolin; Ziehn, Daniel; Speidel, Stefanie; Kather, Jakob Nikolas; Distler, Marius; Saldanha, Oliver Lester
The limited availability of diverse and representative training data poses a critical barrier to the development of clinically relevant computational tools for intraoperative surgical decision support. Surgical procedures are not routinely recorded, and data annotation requires domain expertise, resulting in a scarcity of open-access surgical video datasets with high-quality annotations. Existing datasets are typically limited to single institutions and specific procedures, such as cholecystectomy, and rarely comprise patient-level metadata like demographic characteristics, disease history, or laboratory parameters. The Appendix300 dataset comprises 330 laparoscopic surgery recordings, including 325 full-length laparoscopic appendectomies and 5 control recordings from non-appendectomy procedures in pediatric and adult patients treated at five German centers. The dataset includes patient-level clinical metadata (demographics, medical history, clinical symptoms, preoperative laboratory parameters, and histopathological findings, as well as standardized expert annotations of the laparoscopic grade of appendicitis. This dataset enables novel validation tasks for computer vision in laparoscopic surgery and facilitates simulation of decentralized learning approaches, overall enhancing the breadth and translational relevance of AI-based surgical video analysis.
Filtration and Particle Discrete Data (quartz < 200 µm) for 'Project Development of multivariant structure and process models for filter cakes, combining experimental methods of process engineering with digital computer based methods'
(Technische Universität Bergakademie Freiberg, 2026-04-29) Löwer, Erik
This dataset contains primary experimental data investigating the filtration behavior and particulate properties of quartz particles. The data was generated through separation tests conducted in accordance with the VDI 2762 guideline (cake-forming filtration). The study aims to correlate particle morphology with specific filter cake resistance within a viscous medium. Quartz (SiO2, 2.7 g/cm³) from Strobel Quarzsand GmbH, product name BCS201, was used as the disperse phase. To ensure a defined particle size distribution, the material was pre-classified to a target range of 50 to 200 µm using a Nisshin Turbo Classifier TC-15M fine air classifier. The continuous medium consisted of a binary water-glycerin mixture: Glycerin content: 24 mass percent (wt%) Additive: 25 mM potassium iodide (KI). Both chemicals were sourced in analytical grade from Carl Roth GmbH + Co. KG.
Complementary 3D-characterization data, including CT scans (Computed Tomography) and segmented individual particle data, are archived in the "Parrot" database of the TU Bergakademie Freiberg (https://parrot.tu-freiberg.de/).
Filtration and Particle Discrete Data (glass beads < 160 µm) for 'Project Development of multivariant structure and process models for filter cakes, combining experimental methods of process engineering with digital computer based methods'
(Technische Universität Bergakademie Freiberg, 2026-04-29) Löwer, Erik
This dataset contains primary experimental data investigating the filtration behavior and particulate properties of glass particles, spherical, < 160 µm. The data was generated through separation tests conducted in accordance with the VDI 2762 guideline (cake-forming filtration). The study aims to correlate particle morphology with specific filter cake resistance within a viscous medium. Soda-lime glass (SiO2, 2.55 g/cm³) from Sigmund Lindner GmbH, was used as the disperse phase. To ensure a defined particle size distribution, the material was pre-classified to a target range of 70 to 160 µm using a Nisshin Turbo Classifier TC-15M fine air classifier. The continuous medium consisted of a binary water-glycerin mixture: Glycerin content: 24 mass percent (wt%) Additive: 25 mM potassium iodide (KI). Both chemicals were sourced in analytical grade from Carl Roth GmbH + Co. KG.
Complementary 3D-characterization data, including CT scans (Computed Tomography) and segmented individual particle data, are archived in the "Parrot" database of the TU Bergakademie Freiberg (https://parrot.tu-freiberg.de/).
Sensitivity of Filter Cake Permeability to Systematic Variations in Particle Shape and Size: A Bottom-Up Stochastic Analysis
(Technische Universität Bergakademie Freiberg, 2026-04-28) Löwer, Erik
The data belongs to the corresponding publication "Sensitivity of Filter Cake Permeability to Systematic Variations in Particle Shape and Size: A Bottom-Up Stochastic Analysis" with the following abstract.
A key question in filtration process design is understanding the filtration properties of a specific particle system. Current methods, like the Carman-Kozeny equation, struggle to accurately predict specific cake resistance and capillary pressure from a given particle size distribution, leading to reliance on limited empirical correlations. This poses challenges for process simulation, as the transition from particle characteristics to filter cake properties remains unclear. This work aims to correlate the distribution of multi-dimensional particle properties—both size and shape—with the properties of the resulting 3D filter cake morphology. We use tomographic image data of real filter cakes to validate a stochastic 3D model which describes the relationship between particle properties and multiphase filter cake characteristics using generated virtual particles that statistically resemble the actual data. Validation is provided by filter cakes from two different particle systems: spherical glass and broken quartz particles ranging in size from 40 to 300 μm with sphericity values from 0.5 to 1. Artificial, but realistic particles following the same particle property distributions are utilized to construct virtual filter cake structures using a forced bias algorithm, which statistically represent actual cake structures. The generated virtual cake structures allow for deriving trends in permeability by systematically varying particle properties virtually.
The dataset provides the used raw data and the generated artifical cake structures which were used for the correlation of several particle, structure and process parameters of the investigated filtration process.