SpatialDataAgent: Autonomous Spatial Omics Data Curation at Decade Scale
Fragmented metadata in spatial omics archives has rendered large volumes of multimodal molecular-histological data inaccessible as dark data. Here, we introduce SpatialDataAgent, an agentic workflow for autonomous spatial omics data curation, combining schema-constrained evidence evaluation with a self-refining standardization agent. Applied to a decade of GEO records, SpatialDataAgent identified 769 paired H&E-spatial transcriptomics (ST) datasets, representing a 6.4-fold scale expansion over existing manually curated baselines. Within the benchmarking window, the framework achieved a 141% increase in high-confidence Class A paired datasets. We further assembled a recent high-confidence subset into HESRT, a standardized datalake containing 29.2 million spots/cells, establishing a blueprint for evidence-grounded autonomous curation of multimodal biomedical archives.