Lori J. Abendroth1, Daryl Herzmann2 and Landon Bunderson2, (1)Iowa State University, Iowa State University, Ames, IA (2)Iowa State University, Ames, IA
The Sustainable Corn Team (USDA-NIFA funded "Climate and Corn-based Cropping Systems Coordinated Agricultural Project") is comprised of 140 scientists, staff, and students across 9 states and 11 institutions. This team is working towards adaptive and mitigative strategies for corn-based cropping systems to climate change in the Midwest through comprehensive research including 35 agricultural research sites (55 treatments and 95 data variables total), ~5000 farmer survey, and 160 farmer interviews. A centralized database was developed to serve the needs of the researchers for importing, accessing, and exporting data sets. System requirements included the need for web applications that would allow the team to self-manage, decode disciplinary “languages”, flexibility to allow for quantitative and qualitative data types collected at different frequencies and for site variation, and highly involved management by the data team. Because of these factors, we choose a combined model based on a traditional relational database and leveraging of the Cloud. Data are entered via two mechanisms including customized interfaces and site-specific spreadsheets which support data versioning, simultaneous editing, and easy export to other formats. Scripts have been developed to programically interface with these spreadsheets. These scripts download the raw data from the spreadsheets into a traditional relational database housed at ISU for aggregation and quality control. We have implemented in phases with functions released to the team as made available to limit delays and bottlenecks. The overall approach to data management for this team has brought about quicker entry of data, increased user familiarity and ownership, increased accountability of researchers to colleagues via "data dashboards", and enabled project work groups to discuss and review data easily. The conceptual approach, development, implementation, and indicators of use are presented here while keeping the overall goal in mind of advancing the team's scientific efforts.