WOOSTER, Ohio — A conference based on numbers and data sets may seem like a dry — perhaps boring — topic for a group of professional researchers.
Such was the main topic at the annual research conference April 24 at the Ohio Agricultural Research and Development Center. And, despite the dismal nature of numbers, no one fell asleep during the event, nor anything of the kind.
Instead, researchers got a fresh update on a topic that will define their work for the foreseeable future: “big data.”
The term is loosely defined, but generally refers to sets of data and numerical findings that are complex, take up a lot of storage space, and that must be cautiously and analytically interpreted.
The use for big data in today’s world are many — preventing and treating disease, making business decisions, protecting national security and making decisions that affect yield and profitability for farmers.
Data matters
Sylvie Brouder, agronomy professor at Purdue University, said the divide between big data and conventional data is not always clear, and what was considered big data in the past, may very well be conventional data today.
But wherever you draw the line, Brouder’s point is that data is a big deal, and will continue to play a major role in both university research and the private sector.
However, there are some “big” problems with big data, especially in agriculture. One is, while the data is often available, it’s not always accessible.
This can be due to a variety of reasons, including the data wasn’t published, it wasn’t stored where others could access it, or it may have relied on units or measurements that were not standardized, or not easily converted by the person trying to access the data.
“You (researchers) have to get it out there,” she said. “We want our knowledge to be translated into rational policy and useful information for users because that’s how we get our impact.”
Part of the problem, Brouder said, is philosophical. Researchers often believe the data they develop address one specific research question — but are hesitant to allow that data to be applied to other research questions.
Understandable terms
Brouder said data, like anything, can be taken out of context, but at the same time, it needs to be standardized to the point where people can use it in a credible, accurate way.
“It (handling data) isn’t necessarily exciting, but when you start to explore the consequences of the absence of that knowledge foundation, it may convert you,” she said. “Because without that, how are students going to look at data and know what to think of it?”
As the years go by, researchers are also faced with challenges of having to manage an ever-increasing amount of data, and the fact that faculty and staff are human beings — who move, change jobs, become ill and yes, even die. If their research isn’t properly documented, it can easily be lost forever.
“Our recommendations have to be living documents,” she said.
One of the things OSU is doing to resolve this issue — and to better prepare students for the realities of big data — is adding an undergraduate major in data analytics.
Studying data
Christopher Hadad, professor of chemistry in OSU’s College of Arts and Sciences, said the first students will embark upon the course this fall, in what should be a promising career path.
He said this will be the first degree of its kind in the country, and said about 400,000 jobs are expected to require people who are skilled in data analytics by 2020.
The program will not only help students study data, but how to apply it usefully.
“The key issue is how do you use data to then be able to make actionable decisions,” he said.
The major will focus on statistics, computer science, communication and all the things graduates will need so they can access, analyze and make real-world sense out of big data.
The major, which is a bachelor’s of science, ends with a capstone program pairing students with a private industry where “real-time application” of big data is needed.
In his opening remarks at the conference, Steve Slack, director of OARDC, said big data “are the guideposts of where we’re going” as an institution, and something that applies across multiple disciplines of study, as well as different institutions.
Bruce McPheron, dean of OSU’s College of Food, Agricultural, and Environmental Sciences, said the university’s biggest opportunity lies in what it can do in private industry.
“The real opportunity for growth is in innovation and how we think about funding partners,” he said. “The big opportunity for us, I believe, is going to be in the private sector.”
Bridging the gap
One challenge, he said, is that the private sector is concerned about making money, and universities are concerned about changing the world.
“We’re (researchers) going to have to learn to speak their (industry’s) language, as we help them learn to speak our language,” he said.
However, big data is one thing they both have in common.
Leasing parking
One of OSU’s most recent big data success stories came in 2012, when the university decided to lease its parking services to a private entity known as CampusParc. This resulted in about $500 million worth of additional revenue that went into the university’s endowment fund.
McPheron said big data compiled and analyzed by OSU is already attracting multiple large companies, and he expects that trend will continue as data compiling and data analytics continue to grow.
