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.
The repository uses persistent identifiers and synchronises with data hubs: DataCite, OpenAIRE, and BASE.
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
Boltz, Joachim
2025-04-12 (1.0.0)
Dataset
Open
We use the https://www.kaggle.com/datasets/imakash3011/customer-personality-analysis dataset to predict whether customers buy in web, store or by catalog.
kaggle
machine learning
Uploaded on May 20, 2025
Bouhamidi, Hachem
2025-04-28 (1.0)
Dataset
Open
Context and Methodology: This dataset was created as part of a sentiment analysis project using enriched Twitter data. The objective was to train and test a machine learning model to automatically classify the sentiment of tweets (e.g., Positive, Negative, Neutral).The data was generated using...
Sentiment Analysis, Twitter Data, Machine Learning, NLP, Classification, HistGradientBoostingClassifier, Text Mining
Uploaded on May 20, 2025
Tsepelakis, Sotirios
;
Sanchez Solis, Barbara
2025-05-14
Dataset
Embargoed
Context and methodology This dataset was created as part of the "Urban Climate Resilience" research project, conducted at the Department of Environmental Sciences, University of Example. The project aims to study temperature and humidity variations in metropolitan areas to better understand the...
Natural sciences
environmental monitoring
Uploaded on May 14, 2025
Akbar, Muhammad Mobeel
2025-05-13
Dataset
Open
Dataset Description for Tour Recommendation Model Context and Methodology: Research Domain/Project:This dataset is part of the Tour Recommendation System project, which focuses on predicting user preferences and ratings for various tourist places and events. It belongs to the field of Machine...
Machine learning
Decision Tree
Tourism Recommendation
Predictive Model
Ratings Prediction
Uploaded on May 14, 2025
Lukas, Kobler
2025-04-28 (1.0.0)
Dataset
Open
This project aims to predict bike rental demand using machine learning, specifically focusing on hourly predictions based on various environmental and temporal features. The dataset used for this analysis is the publicly available "Seoul Bike Sharing Demand" dataset, which includes factors like...
demand forecasting
urban mobility
machine learning
regression with temperature features
xgboost regression
Uploaded on May 13, 2025
