Most data included in evidence-based reviews is reported in journal articles, study reports, and other text-based, narrative documentation. A key component of the systematic review process is data extraction, a manual process to identify and collect data for synthesis across studies. Some hypothesize, if relevant datasets, rather than documents, could be identified using a standardized evidence-based review process, the labor-intensive manual extraction process might be omitted. For our study, we demonstrate the use of evidence-based review methods for collecting climate-smart agricultural datasets. We employ a standardized process to identify relevant data repositories that aggregate or host climate related agricultural datasets. For the resulting repositories, we evaluate search infrastructure and other characteristics to determine capabilities for search. We further assess the use of systematic review methodology practices following search and identify the gaps in data repository infrastructure to support these methods. We will share lessons learned from utilizing evidence-based review methodologies for discovering climate-smart agricultural data and convey the need for addressing these within the scientific community as well as within data repositories, to extend the usefulness of data repositories as an information source.