Coordinate with/collect other approaches on modelling embeddings in LOD

[chiarcos]

As far as we know, there is no mature vocabulary for modelling embeddings and related machine-learning (meta) data as RDF/LOD data in existence. This issue is meant for collecting pointers to any such resources or on-going discussions to develop such vocabularies or resources. Please check once they have been checked for possible implications for our modelling of embeddings.

• Representing and Describing Vector Embeddings and Models in ONNX
• VIS4ML: An Ontology for Visual Analytics Assisted Machine Learning may be consulted for modelling machine learning workflows
• Braga, J., Dias, J. L., & Regateiro, F. (2021). A Machine Learning Ontology. preprint
• Liao, C., Lin, P. H., Verma, G., Vanderbruggen, T., Emani, M., Nan, Z., & Shen, X. (2021, November). HPC Ontology: Towards a Unified Ontology for Managing Training Datasets and AI Models for High-Performance Computing. In 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC) (pp. 69-80). IEEE.
• Sinha, P. K., Gajbe, S. B., Chakraborty, K., Sahoo, S., Debnath, S., & Mahato, S. S. (2021). A Review of Machine Learning Ontologies. International Journal of Information Dissemination and Technology, 11(4), 158-164.