GeoDaRT: Contextual geospatial data infrastructure for distributed on-farm experimentation

On-farm experimentation (OFE) is increasingly recognized as a pathway for developing sustainable and context-specific agricultural practices under real-world production conditions. However, OFE outcomes are difficult to interpret, compare, and aggregate when the environmental and biophysical context of each experiment is not described in a consistent and reproducible way. The main barrier is not only access to public geospatial data, but the repeated transformation of heterogeneous soil, terrain, weather, drought, and satellite products into traceable, analysis-ready covariates linked to agricultural fields and experimental time windows. This study presents the Geospatial Data Retrieval Tool (GeoDaRT), a web-based system that implements a reproducible contextual data workflow for OFE and related agricultural research. GeoDaRT organizes retrieval around experiment-oriented requests consisting of an area of interest, temporal parameters, selected data products, and processing options. The workflow standardizes access, clipping, file formatting, naming, metadata, packaging, and provenance while preserving native source resolution and coordinate reference information where appropriate. GeoDaRT was evaluated through a distributed field-scale analytical-readiness workload involving 200 corn and soybean fields in New York State and the U.S. Midwest over three growing seasons. The system produced 105,984 contextual files representing 600 site-years. These outputs supported an end-to-end multivariate analysis of 19,900 field pairs without custom reformatting. The analytical-readiness workload produced a coherent contextual feature space and demonstrated that GeoDaRT outputs could support residual-tail summaries and mapped interpretation. These results demonstrate that GeoDaRT makes contextual covariate generation more feasible, auditable, and reusable for distributed OFE.