Professor Aaron Quigley, Chair of Human Computer Interaction [HCI], School of Computer Science, University of St Andrews, Scotland - and incoming Head of School of Computer Science and Engineering, University of New South Wales, Sydney, Australia.
Turning 18th century shipping records - written in cursive pen on faded paper - into modern data sets is understandably tricky.
Computer scientist Prof Aaron Quigley was perplexed to suddenly find hundreds of thousands of documented shipments of limes from Canada.
Limes? Really?
It was 2014 and the Dubliner was working as part of an interdisciplinary team on a project called Trading Consequences, which explored the commodities trade under British imperialism 200 years previously.
Trading Consequences was a Digging Into Data funded collaboration between commodity historians, computational linguists, computer scientists and librarians who mined, analysed and visualised information extracted from over 200,000 historical documents.
But the multitude of limes? Nobody on the team could understand why they had popped up in such numbers out of the blue.
“When you went back to the original source document you could see that they were writing the word “time”, not “lime”, but the fashion at the time was to cross the t very lightly. So “time” was turning into “lime”. There were tens of thousands of "limes" and because lime was a type of commodity too it was causing confusion. I guess those are the flaws of data processing.”
Working in an interdisciplinary team has its challenges too - though the reward makes the effort worthwhile - and Prof Quigley has been at the vanguard.
Back in the mid-noughties when he worked at UCD Discovery’s predecessor CASL, interdisciplinary research was in its infancy.
“When I started I was a pure computer scientist. There was little need for interdisciplinary work at time. Now most of our projects require different areas of expertise to tackle problems,” says Prof Quigley, who is now Chair of Human Computer Interaction [HCI] in the School of Computer Science at the University of St Andrews - and the incoming Head of School for the University of New South Wales’s Computer Science and Engineering in Sydney, Australia. He has a degree in Computer Science from Trinity College Dublin and a PhD from the Department of Computer Science from Newcastle University, Australia.
“The main thing I did at CASL (Discovery) is I brought over the Independent Living Team that had previously been in the School of Electrical Engineering. We then had one location for all the interdisciplinary research activities around falls detection and falls prevention in older people.”
He and Prof Paddy Nixon, then Vice Principal of the Faculty of Engineering, Mathematics and Physical Sciences, combined their skills to assess ways of determining somebody’s stability when standing, walking and moving.
“Today most of the bigger questions require that type of transdisciplinary approach - it’s the nature of the general societal challenges we’re facing,” explains Prof Quigley, giving the examples of “wellbeing, sustainability and sustainable societies and creating environments for the future of work”.
HCI is now very transdisciplinary and projects often have teams drawn from myriad academic worlds.
"Everyone needs to learn some aspect of another discipline to make the work progress. You would expect that a physicist should learn about data sets from a data scientist, the data scientist learns from the ethnographer, the ethnographer learns from the cognitive psychologist, the cognitive psychologist learns from the material scientist. Everyone is going to have to learn about something else for the project to progress. So while everyone works as an ambassador for their own discipline, you also have to work to translate that discipline for other people," he says, adding that each member of the team injects their own knowledge into the research.
"If I’m a computer scientist working with a historian, I’m going to learn about their work and they will learn something about the computer sciences side of things. It’s a two-way street. You learn to appreciate and understand how you differ in order for more interconnected work to progress.”
How does it work in practice?
“Traditionally it’s a lot of language acquisition. ‘What do you call that? What do we call that? Why is that important to you?’ You’re looking at the language that people are using to describe problems. Understanding why something is an interesting problem to them is my greatest challenge as a computer scientist. Why is that research question burning them up? I can understand why my problems are interesting to me. But it’s equally important to understand why someone else’s problem is interesting to them.”