AICat: An AI Cataloguing Approach to Support the EU AI Act
Abstract
The European Union's Artificial Intelligence Act (AI Act) requires providers and deployers of high-risk AI applications to register their systems into the EU database, wherein the information should be represented and maintained in an easily-navigable and machine-readable manner. Given the uptake of open data and Semantic Web-based approaches for other EU repositories, in particular the use of the Data Catalogue vocabulary Application Profile (DCAT-AP), a similar solution for managing the EU database of high-risk AI systems is needed. This paper introduces AICat - an extension of DCAT for representing catalogues of AI systems that provides consistency, machine-readability, searchability, and interoperability in managing open metadata regarding AI systems. This open approach to cataloguing ensures transparency, traceability, and accountability in AI application markets beyond the immediate needs of high-risk AI compliance in the EU. AICat is available online at https://w3id.org/aicat under the CC-BY-4.0 license.
Keywords
Cite
@article{arxiv.2501.04014,
title = {AICat: An AI Cataloguing Approach to Support the EU AI Act},
author = {Delaram Golpayegani and Harshvardhan J. Pandit and Dave Lewis},
journal= {arXiv preprint arXiv:2501.04014},
year = {2025}
}
Comments
Presented at 37th International Conference on Legal Knowledge and Information Systems (JURIX) 2024