This study addresses a significant gap in the systematic evaluation of agricultural data sources in South Africa by pursuing three primary objectives. The first objective is to assess and compare the accessibility and usability of agricultural data sources across various provider types operating within the country. The second objective involves evaluating the technical performance of agricultural data websites through automated Lighthouse audits, which measure page loading speed, accessibility compliance for users with disabilities, adherence to web development best practices, and search engine discoverability. The third objective is to determine the representativeness of the current agricultural information landscape by identifying coverage patterns across subsectors, commodities, spatial levels, time periods, and critical agricultural variables, thereby exposing gaps in the national data ecosystem. In alignment with these objectives, the study makes three key contributions: it offers a comprehensive empirical assessment of accessibility and usability barriers within South Africa's agricultural data landscape; it provides detailed coverage metrics that highlight critical under-represented areas such as gender-disaggregated data, smallholder farmer information, and sub-provincial spatial granularity; and it presents evidence-based policy recommendations for enhancing agricultural data governance through the adoption of national data standards, mandatory update protocols, open licensing, and bandwidth-aware delivery formats that prioritize machine-readable data over PDF-only publications.
Bernard (Thu,) studied this question.