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
FairBotBench
(Hochschule für Technik und Wirtschaft Dresden, 2025-07-03) Janusko, Tamás; Bochnia, Ricardo; Hempel, Gunnar; Tomschke, Steffen; Anke, Jürgen; Thiele, Maik
This paper presents a concept for building a benchmark dataset to systematically evaluate chatbot responses in e-commerce with respect to ethical quality dimensions such as bias, toxicity and personalization. The core approach involves generating neutral base dialogues of varying lengths, which are then expanded into more problematic variants and enriched with linguistic diversity. The data is annotated by humans through a multi-stage process. The resulting dataset is intended to support the development and calibration of ethical AI components. To increase utility an english translation of the dataset is provided.
Item
Open Access
Dimensioning of Auxiliary Systems for Ammonia-Fueled Vessels
(Technische Universität Dresden, 2025-07-02) Christoff, Bruno
This dataset is part of NH3CRAFT Deliverable D5.4: Parametrized Test-Benchmark with Dataset of Desktop Studies. It contains the dimensioning of the main auxiliary systems for ammonia-fueled vessels. The dataset includes data for the dimensioning of the pipes, low- and high-pressure pumps, recirculation and buffer tanks, heaters and nitrogen supply requirements.
Item
Open Access
Estimation of fuel storage capacity for Ammonia-Fueled Vessels
(Technische Universität Dresden, 2025-07-02) Christoff, Bruno
This dataset is part of NH3CRAFT Deliverable D5.4: Parametrized Test-Benchmark with Dataset of Desktop Studies. It was generated using a MATLAB/Simulink model developed for a digital design platform supporting the conceptual development of ammonia-fueled ships. The dataset enables parametric studies focused on estimating the ammonia fuel storage capacity and operational profiles of vessels under different scenarios. The model estimates the fuel storage capacity considering the vessel’s operational profile, the vessel’s available installation spaces, and tank configuration options. The operational profile includes engine power, vessel speed, and days of operation. The vessel dimensions take into account the available installation spaces and the breadth of the vessel. Several tank configuration options are explored, including the use of Twenty-foot Equivalent Unit (TEU) and Forty-foot Equivalent Unit (FEU) tanks—made of either metallic or composite materials—and placement strategies such as horizontal placement (with and without stacking allowance) and vertical placement. The key outputs include the tank capacity per installation space in cubic meters, the vessel range (or coverage) per installation space in nautical miles, and the number of tanks per installation space. vessel range per installation space (nautical miles), and the number of tanks per installation space
Item
Open Access
SivaS Project Results: Traffic Observation Data and Exemplary Subset of Master Database
(Technische Universität Dresden, 2025-06-30) Kannan, Rajagopalan; Prokop, Günther; Kollascheck, Armin; Gerike, Regine; Stoller, André; Böhme, Tobias
This dataset comprises JSON files and .mp4 video recordings that collectively form the foundation of a centralized database for traffic observations, referred to as the SivaS Master Database. Included in the dataset are: (i) a subset of the raw traffic observation data, (ii) JSON schemas defining the standardized data structure for traffic data storage, (iii) the hierarchical folder framework for organizing such data, and (iv) an exemplary implementation of the standardized database. Given the complexity of the raw data and the substantial effort involved in converting it into the standardized structure, only a limited sample dataset was manually curated and prepared. The SivaS Master Database was created by transforming a subset of the raw traffic data collected during the project into the established database, designed to support integration from various acquisition systems. The dataset includes traffic observations obtained through three different modalities: drones, stationary pole-mounted cameras, and sensor-equipped NDS (Naturalistic Driving Study) vehicles. Specifically, it features over 60 minutes of video recordings from a junction in the city of Dresden, captured simultaneously by three stationary cameras. Additionally, it contains more than 30 minutes of drone-based video footage from two separate junctions in the city of Hoyerswerda. It also includes vehicle positioning data collected by a sensor-equipped observation vehicle, formatted according to the standardized structure, from traffic observations conducted in Hoyerswerda.
Item
Open Access
Research Data Management Handbook for SPP100+
(Technische Universität Dresden, 2025-06-27) Aqlan , Samar; Kang, Chongjie; Eisermann, Cedric
This handbook provides a comprehensive guide to research data management (RDM) for the joint project SPP100+, an interdisciplinary initiative that brings together five research clusters and approximately 19 subprojects. The project addresses the urgent need for earlier and more effective preventive maintenance of complex structural systems—such as those found in transport infrastructure—by enabling predictive insights into degradation processes. As structures age, their condition deteriorates increasingly rapidly, making early detection and intervention crucial. SPP100+ focuses on advancing the collection, integration, and evaluation of data related to geometry, material properties, stress, and ageing. Central to this effort is the concept of the digital twin, which allows for real-time, data-driven decision-making in the maintenance and operation of unique, large-scale infrastructure. This handbook outlines the RDM strategies tailored to the project's unique demands, supporting consistent, interoperable, and reusable data practices across all contributing research units.