TU Wien Research Data (Test Instance) Repository
Share your research. Grow its impact. Keep it safe for the future. Our institutional platform enables you, as a TU Wien researcher or affiliated partner, to manage and publish your data and code with ease. Every upload is assigned a DOI and a usage license, ensuring compliance with the FAIR principles and funder requirements. You remain in control of your data, deciding whether to share it openly, restrict access to selected collaborators, or keep it private until you're ready. Throughout the process, you'll benefit from the personal support of our dedicated repository team.
Recent uploads
Held, Johannes ; Gerez, Kyzer ; Zakaryan, Gevorg ; Ahmad, Habib
2026-05-30 (2.0.0) Data Management Plan Open
The Final Data Management Plan (DMP) and machine-actionable DMP (maDMP) represent the comprehensive documentation of the 'Predicting Urban Traffic Congestion' project’s data lifecycle. Following the RDA DMP Common Standard 1.2, these deliverables provide a formal, interoperable record of the...
Logan, Charles ; El Dib, Yehea ; Höfinger, Balthasar ; Hardt, Julian
2026-05-30 (2.0) Data Management Plan Open
DMP: UK Collision Severity Prediction Predicting the severity of road traffic collisions in the United Kingdom using the Department for Transport's STATS19 open data (2020–2024). Project context Developed as part of the FAIR Data Science course (DaSt 2026) at TU Wien. Abstract The UK government...
Civil engineering
Computer and information sciences
Uploaded on June 1, 2026
Hamza, Ameer ; Akhtar, Haseeb ; Revay, Matus ; Vandák, Gregor
2026-05-28 Data Management Plan Open
This record contains the final Data Management Plan (DMP) and machine-actionable DMP (maDMP) for the project "Analyzing the Connection Between Financial Earnings and Life Satisfaction in EU countries", submitted as part of the TU Wien Data Stewardship course 2026. The project analyses the...
Edeh, Ekene
2026-06-01 (v2.0.0) Data Management Plan Open
Final Data Management Plan (DMP) and machine-actionable DMP (maDMP) for the FAIR Data Science course experiment at TU Wien (2026). The project predicts the end-of-season transfer market value of football players in millions EUR using XGBoost regression trained on two openly licensed datasets...
data management plan, FAIR data science, football player valuation, market value prediction, XGBoost, machine learning, DBRepo, open science, RO-Crate, maDMP, transfer market
Uploaded on June 1, 2026
Jaleel, Usman
2026-05-06 Dataset Open
Trained machine learning model for FAIR-compliant housing price prediction experiment using reproducible workflows, semantic metadata, SQL-based preprocessing, and FAIR data science principles. The repository includes metadata standards, ontology mappings, reproducibility documentation, Docker...
housing machine learning FAIR prediction regression
Uploaded on June 1, 2026
