MLSeascape is a web application that provides an abstraction layer for discovering ML metadata from online platforms, leveraging knowledge graphs. It serves diverse ML components and is able to demonstrate their properties and relationships between them, as well as to provide the original sources they are found. The metadata are retrieved from MLSea-KG, the largest publicly availble knowledge graph of machine learning metadata to date.
MLSeascape currently serves metadata from:
MLSeascape allows users to search for different types of ML artifacts including:
- Datasets
- Models
- Software
- Tasks
- Algorithms
- Implementations
- Publications
Users first select the type of ML artifact (e.g., datasets) they are interested to search for and input a related keyword.
MLSeascape then presents potential matches for their search input in the MLSea-KG.
When the users select one of the matches, they are led to a new page that presents all generic metadata about their choice (e.g., date published, creators, description, original source) as well as related ML entities (e.g., similar datasets, related software, related ML tasks, publications) for the corresponding artifact.
Ioannis Dasoulas: ioannis.dasoulas@kuleuven.be
Anastasia Dimou: anastasia.dimou@kuleuven.be