Vast amounts of data are being collected throughout the food system: on the farm, in processing, during distribution, at retail, in the home, and in the public health system. There is increasing interest in how to leverage these diverse sources of “big data” to identify and manage food safety risks in both the public and private sectors. The siloed nature of data sources and the persistent lack of data sharing within and between sectors are barriers that need to be overcome, but they are not the only challenges. Although the potential power of big data is widely recognized, many struggle with how to realize that power. 

Big data analytics, including statistical methods and data visualization tools, are needed to transform data into actionable information that can support risk-based decision making.  A plethora of analytic tools—including synthetic populations, geospatial agent-based models, time-series analysis, and forecasting—have been used to analyze trends, as well as to detect, predict, mitigate, and rank risks.

This symposium will discuss the potential of big data analytic tools for improving food safety and provide attendees with practical examples of how these tools have been applied in the food safety arena. The symposium will conclude with an interactive discussion between presenters and attendees.

Presentations