Bridging the Big Data Divide

The future of agriculture can largely be described in two words: big data. Unprecedented amounts of data have already been collected from satellites, drones, underground sensors, and all forms of on-the-ground machinery—and much more data is needed to drive better research, public policy and decisions in the field.

Right now, few people can use this agricultural data to its maximum potential, but the new and innovative Agricultural Data Science Certificate course offered through NC State’s College of Agriculture and Life Sciences will create graduates who can do just that—and more.

Daniela Jones, research assistant professor at NC State’s College of Agriculture and Life Sciences (CALS) and coordinator of the new 12-credit certificate program, says these students will be well positioned to help solve some of the world’s grandest issues in agriculture.

“Agriculture is a big industry that we all rely on for food; it is also highly dependent on the environment and changes in our climate,” said Jones. “Our students will use data analytics to help solve data-intensive grand societal challenges such as increasing crop yields and enhancing agricultural and environmental sustainability.” 

The Ag Data Sciences Certificate program was developed in cooperation between CALS, the College of Science, and the College of Engineering. Like many data science programs, it will combine data management, analysis, computer science and statistical training. But unlike other programs, this training will be applied to the agricultural, food, and life sciences.

John Dole, associate dean and director for academic programs, says the new certificate program supports a sector in the agricultural and life science industries that is clearly growing.  

“We recently surveyed a wide range of agricultural and life science companies. More than 93% said they expect at least one or more future positions will either require or benefit from ag data science management training,” said Dole. “And 71% expected the need for ag data management expertise will grow substantially in the next five to 10 years.”

Synthesizing Knowledge

Jones, who designed the Ag Data Science Certificate program, says it bridges a knowledge divide between the fields of data science and agriculture, as few individuals currently have knowledge in both areas.  

To fill this gap, the program brings together post-baccalaureate and graduate students with two general backgrounds: those with degrees in the agriculture, food or life sciences who want to use and manage data collected from the field—and those with degrees in computer science, math or statistics who want to apply their data science skills to agriculture or agriculture-related issues. 

Jones says nearly every student entering the program will have knowledge in either agricultural systems or data analytics, but they will finish the course stronger in both areas. 

“Most data modelers are not familiar with the complexities of agriculture. It’s full of variables, like temperature, precipitation and soil; and plants don’t grow the same in different places. Computer programmers are not always thinking about how these and other variables affect yield,” said Jones. “By the same token, those who are well-versed in crops and agricultural systems use models based on anecdotal data and what has worked in the past. Our students will learn to look at data in new ways. They will think differently when making predictions or conducting modeling in the agricultural, natural resources, and food spaces. Our hope is to pair a farmer’s common sense with data science techniques and train field-experienced data scientists.”

Jones says students who complete the certificate program will have a strong competitive advantage in the agricultural workspace. 

“Graduates who go on to specialize in agricultural operations will have the experience of analyzing, manipulating, pooling, and applying big datasets to crops and field operations,” said Jones. “Graduates with pure data science backgrounds will enhance their skill sets for dealing with the complexities of the agricultural sector.”

Jumping Fences

From Agriculture to Data Science

Shelly Hunt, a master’s student studying biological and agricultural engineering at NC State, has an educational background in agriculture. She was one of the first students accepted into the Ag Data Science Certificate program. She says the certificate will clearly show potential employers her area of specialization during graduate school. 

“My master’s degree will say ‘biological engineering’; that can mean a lot of things,” Hunt said. “When you think of bioengineering, data science isn’t what you think of. This certificate shows future employers what I’ve specialized in. It’s easy to convey where my expertise is.”

Hunt, who is halfway through the certificate program, says the courses allow her to directly apply statistics, data collection, and other important aspects of data science to real-world projects in the field. This includes her work on NC State’s Sweetpotato Analytics for Produce Provenance and Scanning (Sweet-APPS) research project, where she and a team of researchers collect data and use machine learning to understand what governs the shapes and characteristics of sweetpotatoes as they grow in the field. The program helps to solve the issue of food waste, as many misshapen sweetpotatoes are never harvested. 

“We’re encouraged to use real-life data from hands-on research projects,” Hunt said. “It’s making me more efficient with writing code, and it’s showing me how to use new and exciting tools and technologies.” 

After graduate school, Hunt plans to be an analyst for a major ag company or a big company with an agriculture division. 

“I’d love to be able to continue doing outreach to actual producers,” Hunt said. “That’s one part of my research that I love: being able to talk with them. I want a job where I can assess customer or producer needs and create the data driven tools to support them and their operations.”

From Data Science to Agriculture

Shana McDowell comes from a background in math and data science. The senior data tech at Duke University’s Human Vaccine Institute helps research the protein spikes on two of the world’s most notorious viruses: COVID-19 and HIV. 

At the end of August, she will leave her job at Duke to get her PhD degree in biological and agricultural engineering at NC State. As part of her studies, she enrolled in the Ag Data Science Certificate program.

“I was drawn to the certificate after learning about it in an email from Dr. Dani Jones; I didn’t realize there was a lane for data scientists in agriculture,” McDowell said. “But I like to work with data and make sense of it, and I always loved working in new and different disciplines.”

Like Hunt, McDowell will be working on the Sweet-APPS project, using math and her computational science backgrounds to solve a real-world issue in agriculture.  

When asked about her future, McDowell says she is undecided between industry and teaching. 

“I taught high school for five years,” McDowell said. “I have a love for teaching and breaking down different concepts, and I can see myself teaching again. But I can also see myself doing industry work. I’m stuck between the two right now.” 

Jones says the Ag Data Science Certificate program will build a close community of experts, like McDowell and Hunt, who can use analytics to help solve some of the grandest issues in the agricultural and plant science fields today. 

“This certificate program is well positioned for NC State,” said Jones. “A lot of our instructors are also researchers working to solve some of the biggest issues facing the world today through the N.C. Plant Science Initiative. These students will have the opportunity to take on food insecurity, sustainable agriculture, and climate change.”

A Quantifiable Demand

NC State surveyed 254 individuals working in a broad range of agriculture and life science companies. Of the 41% who responded:

• 87% said that one or more of employees in their company would like to get additional training in agriculture data science management. 
• 93% indicated that one or more future positions in their company would require or benefit from training in agricultural data science management. 
• 71% thought that the need for people with training in agricultural data management will increase substantially over the next five to 10 years.