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arxiv:2608.02949

On the missing data layer and a potential solution

Published on Aug 3
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Abstract

DataHub proposes a task-first ontology-based infrastructure to organize, discover, and expand Latin American AI datasets.

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.

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