This page hosts some of curated datasets that power our workflows. See our Hugging Face profile for more information. See also [Leaderboard].
Data for: Temporal Neighborhood-level Material Wealth Maps of Africa (1990-2019)
Description: The data product consists of continent-wide maps of material-asset wealth across Africa from 1990-2019, created by using multi-temporal satellite imagery at the neighborhood level.
[Dataverse] [Hugging Face] [Article]
Data for: Image-based Treatment-effect Heterogeneity
Description: Repository contains experimental data for an anti-poverty intervention in Uganda, along with geo-referenced satellite imagery for each experimental unit.
[Dataverse] [Hugging Face] [Article]
Data for: Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty?
Description: Repository contains more than 60,000 geolocated DHS clusters across Africa paired with high-resolution Landsat satellite images, textual descriptions generated by LLMs conditioned on location and year, and textual data retrieved by an AI search agent from web sources, labeled with International Wealth Index (IWI) scores. Data are useful for training multimodal models for poverty prediction, analyzing representational convergence between vision and language modalities, and benchmarking generalization in socio-economic AI. The dataset enables investigations into the Platonic Representation Hypothesis and agent-induced novelty in development contexts.
[Hugging Face] [Preprint]
Data for: Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities
Description: Repository contains observational data for aid interventions in Nigeria, along with geo-referenced satellite imagery for each observational unit.
[Dataverse] [Hugging Face] [Preprint]
Planetary Experiments Repository (Geo-located RCTs)
Description: A collection of Randomized Controlled Trials (RCTs) suitable for linking with satellite imagery (Planetary Causal Inference – PCI). Key features include geo-located units (village/block/ward level), defined control/treatment groups, sufficient sample size/spread, and documented design. Includes studies on poverty, cash transfers, voter turnout, environmental interventions.
[Link]
