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Introduction to data management

Kayla meets up with Matthew Good from the University Library to talk about the data lifecycle and what components are in there.
Hi Matthew, so we’re here at a library, and we’re here to talk to Matthew who is a librarian here about data management. So first off, how would you describe data management? Basically it’s the process of reviewing everything you do around organising, documenting, and working with your data. And the research project, basically. And when we talk about data, we can see things like your observational data, you get from instruments. Or experimental data, computational data, that comes up from research or– sorry, computer programmes. And that sort of thing. But also records, so it can be the administrative records you’re creating for your project. Or it can be other records that you are maybe using the data source, and that sort of thing.
So anything that goes into our movement analysis projects is classified as data. Yeah, basically. OK, that makes sense. So what components are involved in data management? Well basically you’re going to be including things about– how are you going to be organising your files, organising your data? How are you going to be collecting your data, and the different data sets that you’re going to be working with. It’s also going to be looking at where you’re going to be storing your data. Is it going to be stored in the cloud, is going to be stored in some other kind of solution? How you maintain the quality of your data. So kind of the process as you think around that.
How are you going to comply with legal standards, and requirements? If for example, you’re working with copyright information, or if you’re working with private information, or classified information, to make sure you have a plan for that. And basically, how are you going to be kind of– just working with your data, throughout the process. OK. So I’m assuming the process is some sort of a cycle? I’ve heard what a data lifecycle is, could you please explain it? Sure. Yeah so basically you’re starting with the planning of your project. So making sure that you kind of know what data you’re going to be collecting, and what methods you’re going to be using for your project.
And then using that to maybe potentially search for data sets that might be existing already and available. And then actually going out and collecting your data. And what methods you’re going to be using for that, and what equipment maybe you might be needing for collecting your data. So in any case, the motion capture lab, so you’re looking at the motion capture cameras, and the suits, and that sort of thing. So you can also think about documenting– if you’re doing, for example EEG type stuff, making sure that you have the sensors and understanding what sensors you’re using. What kind of outputs are coming from that.
You could be– also from eye tracking with the cameras, what kind of headsets you’re using to track the eyes, or what kind of outputs come from there. If it’s proprietary formats, if you’re going to convert it to a nonproprietary format. So that you can then archive that in a better way. We also like the MRI, that you also have in your labs. That you’re taking of the fMRI images, and how you’re going to be dealing with the files afterwards, and what the metadata is required, for example, for that. After that you’re going to be cleaning, and processing, and documenting that data.
So making sure that the quality’s there, and it’s actually going to be suitable to analysis, which is the next step. Which also then produces its own set of data, that you have to manage appropriately, right? So it kind of goes back to this whole cleaning, and processing, and documenting process. So then after analysis, then what you’re going to be doing is sharing that data openly. Because that’s more and more of a requirement these days, with funders requiring that you share your data sets openly. And then archiving it, in somewhere to make it publicly available. Well that’s– the parts that can be made publicly available, made publicly available. That makes sense. I assume there’s some specific documents?
Now I know that each group may have certain ones, or each institution might require different ones, but what are our kind of main types of documents, that you might have? As far as the data management plan? Yeah. So that’s kind of this one document, that’s kind of the most important around data management. As everybody calls it a data management plan. And it kind of captures all these different components of the data management process, that you’re looking for. So if you’re looking at describing in there, specifically your data sets, and then using it talking about organisation, and that sort of thing. And it should be a live document, something that’s updated over time.
You may not know at the very beginning of your research what data sets or what equipment you’re going to be needing. But it should be a process, and should be a planning process, that then leads to creating this plan that gets updated over time. OK so if say, I win the lottery halfway through my project, and– You quit. –just quit. Somebody else can come update the data management plan, and keep continuing on my research. They can basically take your project, and continue with it, because everything will be– well, should be documented, hopefully. And that they can understand all the different files and analysis you conducted on your research up to that point.
So they can just pick it up, and go well, maybe after a month or two of reviewing everything, but yeah. Yeah, they should be able to do that. OK, what’s the best way to get started with data management? Contacting your resource person. So asking your colleagues, who do should I talk to? Often the university library will be a very good place for that, because they’ll have some aspect of training in data management. So they’re usually a good place to start. If not, there should be a local data manager that you can usually contact. And also help you with some of the more– or a lab manager like yourself, which can help you with some of the process as well.
So if not, there usually is some web pages available, and there’s also a bunch of resources, I’m sure, at the bottom of this video where you can– Yeah, yeah so we’ll put resources in the links of our articles, as well. All right great, is there anything else that people need to know to get started with data management? Make sure you get that plan in place, and make sure you talk to your colleagues about it. OK, all right, thank you for your time. Thank you.

Kayla meets up with Matthew Good from the University Library to talk about the data lifecycle and what components are in there.

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Motion Capture: The Art of Studying Human Activity

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