ModelSet is a dataset composed of 5,460 Ecore and 5,120 UML labelled models, making a total of 10,580 models. Ecore models have been collected from GitHub, whereas UML models have been retrieved from GenMyModel repositories.
The main label of ModelSet is named category, which represents a type of models sharing a similar application domain. We also assigned other labels to complement the metadata of the models (e.g., purpose, notation or tool). We believe that most of the labels we used are self-descriptive and we invited you to explore the dataset and labels.
Please, check out the following resources to use the dataset.
- Main GitHub repository which includes the release packages
- Paper: ModelSet: a dataset for machine learning in model-driven engineering
- Blog post with an step-by-step example
This dataset is maintained by José Antonio Hernández López, Javier Cánovas Izquierdo and Jesús Sánchez Cuadrado.
You can browse the models included in ModelSet by filtering via category. Once the models are listed, click on the name of the model to expand the information and explore the data.
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