On 21 March 2024 from 10:00 until 11:30 CET the introductory webinar on MLDCAT-AP will be held.
In the current semantic landscape there is a lack of semantic interoperability regarding assets related to machine learning models. MLDCAT-AP (Machine Learning DCAT-AP) is a prototype application profile that extends DCAT-AP in the field of machine learning. It aims to describe machine learning models, together with their datasets, quality measured on the datasets and citing papers. It has been originally developed in collaboration with OpenML, who has implemented the model as part of a pilot program.
The objective of this webinar is to receive feedback on the model and explore the interest from the community regarding their use cases for the model.
More information and issues on MLDCAT-AP can be found on the GitHub page.
The formal invitation for the webinar will be sent out shortly.
Agenda
Concretely, the following topics will be discussed:
- Introduction
- The value of semantic interoperability
- Context (OpenML) and objectives of MLDCAT-AP
- OpenML - Guest presentation
- Introduce the model
- Q&A and feedback