When an astronomer from the University of Toronto Bryan gaensler looks up at the night sky, he doesn’t just see stars – he sees data. Big Data.

Bryan gaensler
(photo courtesy of the Dunlap Institute)

So big, in fact, that his current research into tracking the baffling “rapid radio bursts” (FRBs) bombarding Earth across the universe requires the capture of more data per second than all Internet traffic in Canada.

“It’s probably the most exciting thing in astronomy right now, and it’s a complete mystery,” says Gaensler, director of the Dunlap Institute of Astronomy and Astrophysics at the University of Toronto and holder of the the Canada Research Chair in Radio Astronomy. “Randomly, maybe once a minute, there’s this incredibly bright flash of radio waves – like a millisecond burst of static – coming from random directions across the sky.

“We now know that they are at very great distances, up to billions of light years, so they must be incredibly powerful to be seen this far.”

The U of T is a world leader in FRB research, using the CHIME multi-university radio telescope in the Okanagan region of British Columbia and a U of T supercomputer. Yet despite the impressive technology, many significant challenges remain.

“It’s a huge calculus and processing problem that is holding us back,” he says. “We record more than all of Canada’s Internet, every day, every second. And because there isn’t a hard drive big enough or fast enough to actually store this data, we end up throwing away most of it. We would obviously like to manage data better, which requires better equipment and better algorithms and just better ways of thinking about data. “

With the establishment of the University of Toronto’s Data Sciences Institute (DSI), Gaensler and his colleagues now have a new place to turn for help. The institute, which is hosting a launch event tomorrow, is designed to help the university’s many academic experts in various disciplines team up with statisticians, computer scientists, data engineers and other digital experts to create Powerful research findings that can solve a wide range of problems – from shedding light on interstellar mysteries to finding life-saving genetic therapies.

“The way forward is to bring together new teams of astronomers, computer scientists, artificial intelligence experts and statisticians who can come up with new approaches optimized to answer specific scientific questions that we currently don’t know how to tackle. “Gaensler said.

The Data Sciences Institute is just one of nearly two dozen Institutional Strategic Initiatives (ISIs) launched by the University of Toronto to address complex and real challenges that cut across areas of expertise. Each initiative brings together a flexible and multidisciplinary team of researchers, students and partners from industry, government and the community to take on a “big challenge”.

“We bring together individuals at the intersection of traditional disciplinary fields and computer and data sciences,” says Lisa Strug, Director of the Data Sciences Institute and Professor in the Departments of Statistical Sciences and Computer Science in the Faculty of Arts and Sciences, and Principal Investigator at the Hospital for Sick Children Research Institute.

She notes that the U of T has world-renowned experts in fields such as medicine, health, social sciences, astrophysics and the arts, and “some of the best departments in the world in allied fields of science. data science like statistics, mathematics, computer science. science and engineering.

Data science techniques can be applied to an almost endless variety of academic issues – from climate change to transportation, from planning to art history. In the literature, Strug says, many works from previous centuries are now digitized, allowing data-driven analysis down to, say, sentence structure.

“New areas of data science are emerging every day,” says Strug, who oversees data-intensive genomics research in complex diseases such as cystic fibrosis which has led to the promise of new drugs to treat the disease. debilitating lung. “We have so many IT disciplinary strengths that we can leverage to define and advance these new areas.

“We want to make sure that professors have access to cutting-edge tools and methodology that allow them to push the boundaries of their field. They may be answering questions they would not have been able to ask before, without this data and without these tools.

A key function of ISD is the creation and funding of Collaborative Research Teams (CRTs) of professors and students from various disciplines who can work together on important projects with stable support.

Gaensler, who already has statisticians on his team, says he relies on CRTs to greatly expand the scope of his work.

“We just made the fruit at hand,” he said. “There are a lot of deeper issues that we haven’t even started on.”

Laura Rosella (photo by Caitlin Free)

In the same way, Laura Rosella, associate professor at the Dalla Lana School of Public Health, says collaborative teams will be a major asset for the university.

“We’re going to dedicate funds to these multidisciplinary interns and post-docs so that we can start building a critical mass of people who can actually translate between these disciplines,” she says. “To solve problems, you need this connection expertise. “

Rosella was instrumental in how Ontario handled COVID-19 in early 2021. By analyzing anonymous cell phone data as well as health information, she and her interdisciplinary team were able to see where the people would move and congregate, then predict in advance likely clusters of the disease that would appear up to two weeks later. His work has helped support the province’s highly successful strategy of targeting so-called “hot spots”.

“We were able to work with various data sources to generate information that is used to
high-level pandemic preparedness and planning, in a way that was not possible before, ”says Rosella, who sits at Ontario’s COVID-19 Modeling Consensus Table. “And we’ve also brought new angles to the data on the social determinants of health that have highlighted the policy actions needed to truly address the disparities in COVID rates.”

Rosella’s population risk tools also include a tool for diabetes, which health systems can use to estimate future disease burden and guide future planning. This includes inputs on the built environment. For example, if people can walk to a new transit stop, Rosella says, increasing exercise can impact diabetes or other illnesses. Potentially, even satellite imagery data could be incorporated into the prediction mix, she says.

In addition to advancing research in a given area, the Data Sciences Institute also seeks to advance equity.

This includes addressing societal inequalities uncovered by data research – including how socio-economic factors can determine who is most likely to contract COVID-19 – and how the research itself is conducted.

For example, Strug says most genomics studies have focused on participants of European descent, although genetic risk factors for various diseases may differ between different ethnicities.

“We need to make sure we develop and implement the research models, tools and designs – and bring together various sources of data – to ensure that our understanding of disease risk is applicable to everyone,” Strug said.

Many algorithms, or the data they use to make predictions, contain unconscious biases that can skew the results – which is why Strug says transparency is vital both to support fairness and to ensure that studies can be reproduced correctly.

Gaensler says ensuring diversity among researchers is also essential.

“My department is very different from the faces I see in the metro,” he says. “It’s not a random sample of Canadian society – it’s very masculine, white, and old, and it’s an issue we need to work on.

Strug hopes the Data Sciences Institute will eventually become a hub for researchers across the university – and beyond.

“There has never been a single entry to university to guide people, so it’s so important for us to be that gateway,” she says.

“We will do everything we can to stay on top of the different fantastic things that are happening in data science and be able to direct people to the right place, as well as provide an inclusive, welcoming and inspiring academic home. “

This article is part of a series on the University of Toronto’s Strategic Institutional Initiatives program – which aims to make life-changing advancements in everything from infectious diseases to social justice – and on the community. research that drives it.