Welcome to TU Wien Research Data (Test Instance)
TU Wien Research Data (Test Instance) is an institutional repository of TU Wien to enable storing, sharing and publishing of digital objects, in particular research data. It facilitates the funders' requirements for open access to research data and the FAIR principles by making research output findable, accessible, interoperable and re-usable. It is developed by the TU Wien Center for Research Data Management and hosted by Campus IT on servers in Vienna, Austria.
The repository uses persistent identifiers and synchronises with data hubs such as DataCite, OpenAIRE, BASE, and search services like Google Dataset Search. Thus, it maximizes the visibility of the uploaded content. TU Wien Research Data (Test Instance) is also listed in FAIRsharing and re3data - registries many funders refer to.
Recent uploads
Jaleel, Usman
2026-04-10 Dataset Open
This dataset is part of a machine learning project in the domain of real estate analytics and urban economics. The purpose of the dataset is to support the prediction of housing prices in European cities using regression models. The dataset was obtained from the European Union Open Data Portal...
Uploaded on April 10, 2026
Chattopadhyay, Sneha
2026-04-09 Dataset Open
The dataset used in this project contains hourly air quality and weather measurements collected in the city of Gijón, Spain, during 2013. It includes variables such as pollutant concentrations (PM2.5, NO₂, CO, O₃, SO₂) and environmental factors like temperature, humidity, wind speed, and...
Uploaded on April 10, 2026
Puthenpurayil Biju, Vijayalakshmi
2026-04-10 Dataset Open
This experiment explores whether Vienna's geographic districts can be predicted from dog breed registration data. The dataset used is the openly licensed hunde-wien.csv, sourced from data.gv.at under a CC BY 4.0 licence, containing dog registration records across the city of Vienna. A Random...
Uploaded on April 10, 2026
El Dib, Yehea
2026-04-09 Dataset Open
Context and Methodology This dataset was created as part of a Data Stewarship course project at TU Wien. The research domain is road safety and supervised machine learning. The project applies three classification models (Decision Tree, Random Forest, and Gradient Boosting) to predict the...
Uploaded on April 9, 2026
Premus, Luka
2026-04-09 Data Management Plan Open
This record contains the Data Management Plan (DMP) for the project "The BMW Danger Index - Predicting Regional Accident Risks based on BMW Registrations". This project utilizes two Slovenian open datasets covering the period from 2019 to 2023. A model binary is created to evaluate whether the...
Uploaded on April 9, 2026
