用开放标准统一管理高风险AI系统目录，提升透明度与可追溯性。
AICat: An AI Cataloguing Approach to Support the EU AI Act
- 基于DCAT扩展出AICat，实现AI系统元数据的机器可读与互操作
- 支持欧盟高风险AI系统注册，确保信息可搜索、可导航
- 适合关注AI合规、数据治理与开放标准的从业者
欧盟人工智能法案要求高风险AI应用的提供者和部署者将其系统注册至欧盟数据库，信息需以易于导航且机器可读的形式呈现。鉴于欧盟其他数据仓库已采用开放数据与语义网络方法，特别是数据目录词汇应用配置（DCAT-AP），亟需类似方案来管理高风险AI系统的欧盟数据库。本文提出AICat——DCAT在AI系统目录上的扩展，提供一致性、机器可读性、可搜索性与互操作性，支持开放元数据的管理。该开放方法不仅满足欧盟高风险AI合规需求，还增强了AI应用市场的透明度、可追溯性与问责性。AICat已通过https://w3id.org/aicat在线发布，采用CC-BY-4.0许可。
原文摘要 · Abstract (English)
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.
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