Dr Gavin Buckingham (Associate Professor in Public Health and Sport Sciences) talks to Dr Chris Tibbs, Research Data Officer at University of Exeter about the different types of research data he works with and best practices for managing research data during your project.
Podcast transcript
Chris Tibbs: Hello and welcome. I'm Dr Chris Tibbs and I'm the University of Research Data Officer, part of the open research team based in the library here at the University of Exeter. My role involves supporting researchers across the university as they work with and manage their research data, and so this episode is going to be all about research data and how best to look after it and manage it during your project. And to discuss all of this, today I have the pleasure to be joined by Dr Gavin Buckingham, an Associate Professor in Public Health and Sport Sciences here at the University of Exeter. So just to start with Gavin, would you like to tell us a little bit about your research and the different types of data that you work with?
Gavin Buckingham: Hi, there, Chris. Yeah, I'm a cognitive psychologist by training, and I'm interested in human perception and human motor control. And I've been looking at this in the context of measuring the movements and forces people apply to pick objects up, and more recently I've been looking at this in the context of immersive virtual reality as well. Now, most of this data takes the form of pretty simple time streams, time series of data, so numbers representing forces or positions of things in multiple dimensions, and their expression over time. So many thousands of lines of data potentially that we then take maybe the largest value or the value at some critical other time points and that reflects some aspect of human behaviour. So that pretty simply is really what it is that we deal with here.
Chris Tibbs:
So thinking about all those types of data that that you're working with, I mean you mentioned, like numerical time series data. I just want to point out that, you know, data can also mean a wide variety of other types of data and many people might not think that they work with data. But generally, when I refer to data, you know, I'm thinking about any sort of information, evidence, materials that are being collected and used for that research. So I’d just like to hear your thoughts on, so when you're thinking about your data and why it's important that you look after your data and you manage your data in terms of helping your research and also then potentially making that data available.
Gavin Buckingham:
Yeah, it's a really interesting question because the pipeline that goes from the stuff that comes out of the apparatus that I used to capture people's data to the things that are subsequently reported in the paper, that's a pretty lengthy pipeline that has many different steps. And those steps can be fairly clearly articulated, but being able to show the consequences of each of those steps, I think is a really key part in terms of people being able to eventually understand your data and make sense of it and use it in other sorts of ways and I really feel that's the narrative I feel most passionately about in many ways. I'm perhaps, slightly selfishly, I'm not so interested in other people finding mistakes that are present in my data, God forbid, but I'm more interested in this resource that was collected that could potentially be a useful thing for other people in ways that I cannot even really imagine. That for me is the really big value I see in my dataset and I work with clinical populations. I work with children, with older adults, typically developing university aged people, all of whom have interesting ways that they interact with the world around them that you know could feed into hitherto unforeseen mechanisms or rehabilitation or technological advances and, you know, I really see sort of the value of data just sitting there waiting for someone to be able to harvest in that way.
Chris Tibbs:
Yeah, all of this sort of potential that's in that data, that you know, doing analysis that are just completely irrelevant, that are completely separate from your research. So when did you sort of first start thinking about making, like managing your data, to make it available so that others could have it, and be able to analyze it? Was this sort of something that you had a discussion with, maybe your supervisor as a PhD student? Was this something that, you know, you sort of just picked up on sort of later during your career?
Gavin Buckingham: Yeah. When I was a PhD student and postdoc, this wasn't really part of the narrative at all. There was no real sense that this is what you would do, but it was actually more to do with the experimental and analytical code: the MATLAB files in my case that I fairly vividly remember asking someone if I could use the MATLAB files to run an expe
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