Data can be found all around us. Businesses like Walmart collect data about purchasing patterns to better understand their customers, while biologists can use data about the human body to study diseases.
Carleton’s new Institute for Data Science, launched in April, is bringing together students and researchers from across all faculties to study how data of all kinds can be used to extract knowledge and information about different subjects – from science and engineering to communications and business.
“It’s a hub to facilitate research,” says Malcolm Butler, dean of Carleton’s Faculty of Science. “It’s a way of bringing people together from across the campus who have interests in data science, getting to know one another to look for opportunities to collaborate, to be a face for Carleton to the external community for collaboration.”
Last year, the university established a collaborative master’s program in data science involving a number of programs housed in different faculties on campus.
Maria Pospelova is a master’s of computer science student who is specializing in data science. Her research focuses on ways to improve the efficiency of Hadoop which is a framework for distributed processing of large data – or “big data.”
“Data science is like the rock star of computer science,” Pospelova says. “Every company now realizes that they have data, they’re collecting data and they need to somehow convert it into information or business profit. And there are just not enough people who are in data science.”
She says Carleton’s data specialization has given her an edge. With a few months left to go before she completes her degree, she’s already been offered a number of jobs as a data scientist.
Frank Dehne, director of the Institute for Data Science, says the goal is to facilitate real-world collaboration between students and local companies, as well as between university departments.
The institute, which sprouted from a partnership with IBM in 2013, is truly a campus-community partnership, “which is one of Carleton’s strengths,” Butler says.
“There’s lots of potential to have that research connected to external partners – government, NGOs, private sector – who are struggling with the questions that big data poses,” he says.
While a few other data science programs exist in Canada, the interdisciplinary nature of Carleton’s initiative is unique.
“In our group for example, my students – the computer science students – they go into the lab and … do experiments with the biochemists to really understand what they’re calculating. You really have to have the knowledge of what you’re trying to extract data on,” Dehne says.
He hopes the institute’s board of directors can foster more real-world collaboration next year and work with other departments. He’s working on expanding to journalism and communications, where data from social media tools could be analyzed to better understand trends and audiences.
The institute also plans to develop workshops, seminars, training sessions and events where the external community could be invited to work with students, and to have a physical meeting space built in Herzberg Building next year.
“The institute does touch everything. So if people are interested, they’re welcomed and encouraged to get involved,” Butler says.
“It’s really something that the whole campus has a connection to.”