Translating Big Data into Smart Data for Veterinary Epidemiology

VanderWaal, Kimberly; Morrison, Robert B.; Neuhauser, Claudia; Vilalta, Carles; Perez, Andres M.

Generating and storing big data are becoming increasingly easy, but we now face challenges in translating the abundance of available data into meaningful information. This challenge, combined with the capability to analyze epidemiological patterns in near real-time, creates a need to develop effective tools and data pipelines to move from simply having "Big Data" into the creation of "Smart data. " Using the four V's as an organizing framework, Collecting and analyzing very large data sets has become increasingly common as technologies for storage and computation advance. For example, research utilizing bioinformatics approaches, detailed data on the demographics and movements of animal populations, and large scale spatial datasets routinely generate terabytes of data, stimulating a new frontier of advanced analytics to handle such data (9) (10) (11) . Here, we do not provide an exhaustive review of the use of high volume datasets in veterinary epidemiology, but rather select a few diverse examples that highlight the potential use of big data to identify high-risk populations.