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match made in MetaData K-State’s Beef Cattle Institute uses big data to reflect real-time research. Story and photos by Audrey Hambright Innovators in data analytics continue to step up in a big way – but it’s not where you might think. The Beef Cattle Institute (BCI) at Kansas State University has a strong history in representing producer and food animal veterinary needs alike, but has recently taken on the likeness to a start-up company in Silicon Valley. How so? It’s using big data to reflect real-time research.
Collecting behind the scenes to get ahead Under the supervision of Dr. David Amrine, BCI research director, the BCI has created a large operational database through strong collaborations with consulting veterinarians and feedyards. The data represents approximately 55 feedyards across the United States or 2.5 million head of cattle on feed. That’s 2.5 million head of cattle for which the BCI is receiving daily updates. To put that into perspective, the USDA reported United States feedlots with capacity of 1,000 or more head totaled 12 million head on Jan. 1, 2021. “It’s a dynamically updated system,” Dr. Amrine says. “The treatments, the new cattle that come in and cattle that leave from that previous day are all uploaded nightly into our data warehouse. Now we have the latest information.” This gives BCI faculty and students conducting research real-time access to information gathering from a digital “data warehouse.” One of the keys to this system is the ability to keep all data confidential and anonymous prior to analysis. Information gained from this system is valuable to the industry because findings are based on real-world information; yet, data are never associated with any individual operation.
A custom-built system Even though the data is collected overnight, developing the infrastructure and background took a bit longer, as it was 28 | wildcatveterinarian
essentially built from the ground up, using only a branded web service as the platform. The system needed to accept both nightly exports from the participating feedyards, then upload that information into the database. Capabilities were expanded during this process, including the ability for the system to upload “clean” data, or data that was not duplicated. “One of the other challenges with the design and implementation of the system is that the format of information coming from the feedlots is not all the same,” Dr. Amrine says. “This adds to the complexity of the system.” Prior to attending veterinary school at Kansas State University, Dr. Amrine worked as a programmer/analyst for several years. During veterinary school he realized he didn’t want to go into traditional clinical practice, but instead found a way to combine his programming and data skills with veterinary medicine. He worked as a data scientist for Adams Land & Cattle in Nebraska for a few years after receiving his Ph.D. in applied epidemiology at K-State. However, it was ultimately the potential to use data contained in the warehouse for advancing predictive analytics research related to the health and performance of beef cattle that attracted Dr. Amrine to the research position at the BCI. “Research using predictive analytics has exploded in the past 10 years – especially in human health and food production – however, the uptake and application to the beef cattle industry has lagged behind,” Dr. Amrine says. He added that large amounts of data are typically needed to accurately explore and apply predictive analytics in the beef cattle industry, and that it has been difficult to accumulate these data. “The data warehouse we have developed has taken us several steps further in the ability to have large datasets available to accurately train and develop machine learning models
