On the missing data layer and a potential solution

Computer Science > Artificial Intelligence [Submitted on 3 Aug 2026] On the missing data layer and a potential solution Francis F Daniel, Mauro Ibañez, Francis Perelman, Marian Basti Latin America is missing two foundational layers of AI infrastructure: the dataset layer and the benchmark layer. This paper targets the dataset layer. The dataset layer faces two compounding problems: discovery and supply. Latin American AI datasets exist but are scattered across platforms with no shared index. Even with perfect indexing, the total volume would remain far below what frontier AI development requires. We propose DataHub: a task-first data infrastructure organized through the ontology /<task?>/<domain?>/<language?>, with mechanisms for dataset discovery, metadata, contribution, licensing, and reuse. Comments: 7 pages Subjects: Artificial Intelligence (cs.AI); Databases (cs.DB) Cite as: arXiv:2608.02949 [cs.AI]   (or arXiv:2608.02949v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2608.02949 Focus to learn more Submission history From: Francis F Daniel [view email] [v1] Mon, 3 Aug 2026 23:26:06 UTC (11 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-08 Change to browse by: cs cs.DB References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)