Data-Driven Synthesis for Investigating Food Systems Resilience to Climate Change

The production, supply, and distribution of our food involves a complex set of interactions between farmers, rural communities, governments, and global commodity markets that link important issues such as environmental quality, agricultural science and technology, health and nutrition, rural livelihoods, and social institutions and equality – all of which will be affected by climate change. The production of actionable science is thus urgently needed to inform and prepare the public for the consequences of climate change for local and global food systems. Access to data that spans multiple sectors/domains and spatial and temporal scales is key to beginning to tackle such complex issues.

As part of the White House’s Climate Data Initiative, the USDA and the National Socio-Environmental Synthesis Center (SESYNC) are launching a new collaboration to catalyze data-driven research to enhance food systems resilience to climate change. To support this collaboration, SESYNC is developing a new “Data to Motivate Synthesis” program designed to engage early career scholars in a highly interactive and dynamic process of real-time data discovery, analysis, and visualization to catalyze new research questions and analyses that would not have otherwise been possible and/or apparent. This program will be supported by an integrated, spatially-enabled cyberinfrastructure that enables the management, intersection, and analysis of large heterogeneous datasets relevant to food systems resilience to climate change. Our approach is to create a series of geospatial abstraction data structures and visualization services that can be used to accelerate analysis and visualization across various socio-economic and environmental datasets (e.g., reconcile census data with remote sensing raster datasets). We describe the application of this approach with a pilot workshop of socio-environmental scholars that will lay the groundwork for the larger SESYNC-USDA collaboration. We discuss the particular challenges of supporting an integrated, repeatable workflow for socio-environmental data synthesis, and the advantages and limitations to using data as a launching point for interdisciplinary research projects.