Title
Query Languages for Neural Networks. (Research)
Abstract
Crucial elements in this methodology are logical data models and declarative query languages. In the new field of
Data Science, large volumes of data are analyzed by machine learning algorithms that produce predictive models
such as neural networks. Over the course of time, large amounts of neural network and training data are produced
in a data science enterprise. For reasons of transparency, accountability, and plain efficiency, these data need to
be managed in a structured manner, just like the data in a classical database system. Thus, the project proposes to
develop new logical data models and declarative query languages for Data Science, with a focus on neural
networks.
We will base our research on past experience in graph data management, type systems, reflection, and automated
verification.
Period of project
01 January 2022 - 31 December 2025