 This is a new project that I've been developing with my colleagues at the Centre for Digital Humanities Research, Bernardo Nunes and Teri Nomeko-Fuller are the other co-creators, co-authors of this site. And the motivation was partly motivated by the shutdown by COVID-19 and its restrictions on a lot of traditional research methodologies in the humanities and social sciences, but it's also sort of something that we've been thinking about doing for a while, and in a way the lockdown was a push for us to get organised. Yeah, so digital humanities is still largely a self-taught field, and listening to these other talks today, I'm realising that we're not really alone in that, that the skill levels are sort of patchy across researchers in a lot of disciplines. But I think humanities researchers often don't really know where to start, and they might not have had much background in being taught to use digital methodologies, and we all use digital resources a lot, increasingly for our research, but the sort of formal training in unusual types of software or Python is something that is really still not happening a lot in humanities, and so it can be really difficult to get started if you're not someone who has a sort of bravery to just jump in and break something. So some of the barriers for researchers in HASS for engaging with digital methods might be that there's no digitised data, you might be still working with the hard copy archive, praying that they digitise it at some point. There can be software expenses, there's a lot of incredible software, but it's often very expensive, and if your university doesn't have a subscription or you are not attached to a university, it can be really hard to get access. But then there's sort of bigger and harder to define barriers. So things like, when you're getting started with digital methods, you often don't know what is easy and what is hard. So you don't know if making a digital map, which is something I do is going to take you a day, a week, a month, three years, and the answer is it can be all of the above. It's also often very hard. People might share something that they've done for their specific research question, but sometimes translating that method to your research data can be really difficult when you're starting out. And also that the perfect data and method don't exist. And so often a lot of existing tutorials are produced by, say, software companies for using their software work with kind of perfect data. And when you go in with your imperfect data and it doesn't work and it breaks and you don't know if you've done something wrong, if it's not the right software. And also, I think there's still a bit of an issue with sort of gatekeepers, people who are kind of like to make things seem a bit harder than they are sometimes and can actually end up putting off novices in jumping in the deep end. And then apart from that, I think, you know, those people are rare, although sometimes they're a little dominant in some areas, but it's also just the conversations are hard. So if you're used to talking about software in a highly technical way or you're not used to doing that at all, just getting started on that conversation is really difficult. Yeah. And so the CDHR, the Centre for Digital Humanities Research is a bit different in that we're just a research centre, we're not a service centre. So we've got one developed, one very overworked developer. And the rest of us are researchers, we're mostly early career researchers. And so we have a focus on also working on our own projects. But we still get a lot of the questions and inquiries from colleagues and students about how to get started with with digital methods. And because we can't roll out a training program, we often end up writing lots of emails, having a lot of coffee with people. And we sort of, this is where the idea came from. We thought, well, you know, I've had five coffees in the last six months to tell people how to use a GIS program for mapping, why don't we turn that into a lesson that can be used by lots of people. And so trying to pitch these lessons at a lot of different levels. And so people who are novices, people who might have some expertise in one area, but they're thinking of sort of shifting it into another area. And trying to really start at that level of where we often start with students or colleagues, where it's not, it's not a kind of intermediate level question, which is often where a lot of the online tutorials seem to start, they assume you've got a data set, they assume you know how to open the terminal on your Mac and type, you know, type of command in. But really a lot of people in in HAS are still starting at a level where they're asking, you know, I've heard you can scrape Twitter, but what is scraping? And how do I do it? And what is R? And so it's sort of get trying to get people started that that we will begin a level. And also to work out how to translate. So people might have seen a project, one, I know in digital mapping that people often talk about in Australia is the Lyndall Ryan's massacre maps at the University of Newcastle. And people say, you know, she's done this incredible thing, you know, is that something I could do with my research data. And so, you know, working out how to translate that to your own project. Yeah, and I guess, and then especially at the moment, a lot of humanities researchers, social science researchers are facing restrictions. And we're probably, you know, even as you know, congratulations, Melvin, people start to open up a bit. We're still looking at no travel, no overseas travel restrictions on face to face workshops with people, concerns about going into different communities and actually doing face to face engagement. And so I think a lot of these new and emerging methodologies are going to be really important going into the future. Yeah, and so the, I want to briefly talk about who we are, because I think it sort of shapes the type of resource that we've built. So we're really small center, that's sort of almost all of us and half the people in those photos are HDR students. So we've got only four academic staff. But we come from a whole range of backgrounds. So I'm as time said in the introduction, I'm a kind of traditionally trained humanities scholar. I worked in archives, there was no training in software or digital methods, everything I learned, I did myself. But we've also got a colleague from computer science, Bernardo is a computer scientist. And so he's coming from that side, but he's very interested in the application of methods like crowdsourcing and link data to humanities topics. Howard Morphy, who's the man in the middle with the great mop of white hair is an anthropologist. And so he represents a sort of profile of an academic who in a way he doesn't do a lot of the digital methods himself, but he sees the potential for them. And he links up with other researchers who can do the hard work of coding up a website or setting up a digital map. And our HDR students are kind of a new kind of hybrid type of humanities student who are often learning on learning as they do their PhDs, how to implement these digital methods. And coming up with really creative ways to use them such as sort of building a crowdsourced archives and things like this or applying link data to Chinese literature. And it's also comes out of our teaching. So we tend to, ANU is a university where we're all meant to do research led teaching, which is sometimes easier, sometimes harder. But we really try and treat a lot of our students as researchers in training. And so we set them to work on what could easily be real world research projects and often do develop into that. And so a lot of what they've been doing over the last couple of years is to work with Glam collections, so libraries, archives, museums in Canberra. And these students are really diverse. There's some of them are computer science students, some of them are fine arts students, some of them are from languages. And so some of them have a lot of experience using digital methodologies. And some of them have absolutely none at all. And so there's no shared base level for skills and knowledge. And so we wanted to also create a resource that these students could use. So if we have a student who says, you know, I'd like to build, you know, a website as part of my project this semester, but I've never done anything more sophisticated than browse the web. There's somewhere for them to start. But equally, if we get a student who already has a background in computer science and is used to working in a way that is a bit more advanced, that we can also sort of point them in the direction of a sort of different set of skills to acquire over the semester. But one of the things we're really keen on is that we don't give, we don't kind of give step by step instructions. And this is partly because there's no one sort of one size fits all, we'd be developing them for every single student. But also because we're trying to encourage the students to understand the process of learning new software. And so it's not a matter of just learning this piece of software, which you can then keep using for the next 20 years, it's that you need to learn a soft piece of software or a method for a specific project. And that's the reality of research or industry work a lot of time. And so, and so our website, and I'll give you a preview in a second of some of the types of things we've been publishing on it, is very much based on giving people kind of introductions and overviews, two things rather than a sort of step by step, you know, use this command, use this command, use this one, because there's a lot of other, I think, really great resources that already do a lot of that online. So yeah, this is the website I've posted. The URL is on there. I've also put it in the shared doc if people want to have a look at it. And so it's free, it's open, we've made it accessible to anyone who wants to use it. And it's designed to be research support and also teaching material support. And so that we're sort of hoping people will use it for teaching as well as research. And that people can dip into it, whether they're teaching a whole program in digital humanities, or if it's say a course where an instructor just wants to introduce a couple of weeks or a single week of learning some digital methodologies relevant to that particular topic. So the lessons are written by experts, I guess, call ourselves experts, but they're also written by people who are kind of newly learning an area. And so we've got some from our recent graduates from our masters. We've got some by our HDR students. And this is partly because we like to include our students in the projects that we do, but also because often people who are just learning a method are in a much better place to point out the things that an expert has forgotten a difficult barrier. So I'm sure a lot of people have the experience of going through a tutorial and getting to a point where it seems as though they've jumped 10 steps and you think, I don't know how to get there. And so yeah, getting some of sort of not not quite beginners, but but people who are currently in the process of learning a new a new method to write those up as well. So what? All right, for time. So I might look at the website in a second. I'll just run through the next one or two slides. So one thing that's really important to us is that these contributions appear reviewed and we're going to have DIYs for each post. And this is partly to kind of help with longevity. They'll be put in our ANU research repository. But it's also in a sort of to have a kind of critical evaluation so that we, you know, all of these overviews will have a little bit of personal bias, I guess, you know, in terms of the way that we use in for our own research, we want them to be relevant to the border community, but we also want this kind of expertise in methods and software skills to be recognized as research expertise. And so not just kind of help that you take away and you use and you apply to your own work, but something that you acknowledge that someone else has spent, you know, time and effort developing this kind of methodology, expertise in this methodology. And so hopefully this will also help us to make it a quality resource in an ongoing way. And so this I will just so can you see everyone can see the website there. And so I just wanted to flick through really quickly. This is my lesson on digital mapping to give you a sense of these types of overviews that we're publishing. And so we've got a video which briefly describes the method for people who like sort of video introductions, which is what a lot of our students are asking for a lot of the time. And then we've kind of got kind of questions like why would you use this? You know, who is this useful for? Because there's nothing worse than sort of putting hours and hours of time into a method and realizing it's gotten a relevance to be all particular research question or your data set. We've got some jargon busting. And so, you know, these things that can trip people up as they get stuck into a new area where they're not too sure what people are talking about. Prerequisite. So what do you need? It's like don't go and buy an expensive piece of software and realize that you don't have the right data set. And then some ways to sort of get started. So like what are the things that you should try first, just to see if this works with your particular research material. And so the idea is to give people a place to get started, to see if this method is worth investing more of time in, to see if a method is worth investing in buying software. Our approach, we're quite inspired by the Programming Historian, which is a publication which offers really detailed lessons for historians and other people in the humanities and social sciences to use different digital methods. And they've got a sort of open source software only policy. And we're not following that in quite the same way because we think there's some areas where the license software will save you time and effort. But you want to make an informed decision about whether it's worth buying it. And then we've got some examples of projects to look at. And a sort of, you know, very short starting point in terms of references, as well as software and resources. And they're very varied. And so as an example with the mapping one, I've got a mixture of something like QGIS, which is a full suite software. It's a very advanced program. But also saying to people, you know, if you just want to get started by dropping some pins on a Google Maps, that is also a way to get started on digital methods. So you don't need to feel as though you have to jump in the deep end with the most sophisticated piece of software or the hardest method. It's a lot of researchers use, you know, off the shelf tools and simple tools to get started. And that that's a really good place to start. And so, yeah, I'll wrap up there. And yeah, happy to answer any questions. Fabulous. Thanks so much, Katrina. It was also