Environmental monitoring programs can generate actionable data that informs management and policy, but they require intentional design of shared data infrastructures that consider the timeline of decision-making activities, the primary audiences they serve, and potential pain points to ensure robust data-to-action systems. The H2Ohio Wetland Monitoring Program (WMP) was established in 2020 to evaluate the nutrient removal effectiveness of varied wetland restoration projects implemented by the Ohio Department of Natural Resources (ODNR). The data stewardship and governance policies for the WMP have focused on strategies and tools that ensure data preservation, guarantee scientific rigor, and optimize efficiencies from data collection to dissemination by adopting FAIR principles. Our data infrastructure has been built in a stepwise iterative process, adapting and improving systems using on-the-ground feedback from data collectors. We have used custom digital surveys to centralize data entry and automated workflows to optimize and document critical data lifecycle steps. We built standardized quality checks to produce verified and integrated datasets. These approaches address challenges with information centralization and standardization, and ensure robust data toward actionable results, repeatable analyses, and usability in other applications.
