- Updated: July 11, 2026
- 1 min read
Nigeria Machinery Dataset: A Low-Resource Industrial Dataset with Domain-Grounded Reasoning
Introducing the Nigeria Machinery dataset, a groundbreaking low‑resource industrial dataset designed to empower AI research and analytics in African economies. This dataset provides 89 machine‑level records across 28 indicators, covering Nigeria’s manufacturing and oil & gas sectors from 2006 to 2025. Each record is fully sourced and decoded via a comprehensive codebook, ensuring transparency and reproducibility.
Key features include:
- Domain‑grounded chain‑of‑thought (CoT) reasoning examples, improving prompt relevance from 1/78 to 94/94.
- Complete provenance for every data point, released under CC‑BY‑4.0.
- Rich metadata covering subsector, year, and source information.
Explore the dataset and download the full package on our UBOS data portal. For detailed methodology and usage guidelines, visit the methodology page.
This resource is ideal for researchers, data scientists, and industry analysts seeking high‑quality, domain‑specific data to train and evaluate language models on numeric and industrial reasoning tasks.
Andrii Bidochko
CTO UBOS
Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.