 Good morning or good afternoon wherever you may be. Thank you for coming today. I would like to begin by acknowledging the traditional owners of the land on which we meet today. For me in Perth that is the Wajuk people of the Noongar nation. I'd like to pay my respects to the elders past, present and future. Thank you for tuning in today. This is the second of a series of webinars that reprise some of the best sessions and discussions from the Australian e-research skilled workforce summit that took place in late July. Today the focus will be on the humanities, arts and social sciences. Sorry, so we have four speakers today. The first presentation will be about general discussion on HASS research capability. Then we'll be hearing from University of Queensland to learn about the language technology and data analysis laboratory. Then Alexis Tindall from the ARDC will give an update on the HASS RDC project and then we'll be opening up the questions at the very end. So first off I would like to introduce Marco Farmi. Marco Farmi is the manager of digital humanities and social sciences at the research computing centre at the University of Queensland. Over to you Marco. Good afternoon everyone and thank you Matias. As Matias said I manage the digital humanities and social sciences program at the University of Queensland. I'm also managing the HASS virtual lab. So the humanities, arts and social sciences data and HASS virtual lab that is funded by ARDC. A couple months ago I was involved in an interest group that was organised as part of the ARDC skills summit and I thought today I'll give you a bit of an account of what happened and towards the end I'll give you some reflections or maybe provocations on some of the issues that we discussed. We encountered at the summit but also things that we've been talking about more generally over the last few months. Myself as well as Ty and Dale Sumner who is my colleague from the HASS virtual lab, Sarah King and Ingrid Mason both from ARNET. So the event was actually organised and led by Ingrid and Sarah, Ty and I were involved in there and we opened the event with a number of questions asking the audience what they think. So I'm sharing with you here some of the slides of the results we got and I'm not going to go through them but I'll give you a few moments for each slide to look at some of the questions that we asked and some of the answers that the community or the group that were at the meeting contributed to. So first we were asking about some of the training that is different about HASS and why HASS could be treated differently from STEM and this is a question I'll come back to towards the end there. So these are some of the answers that people have volunteered for us. Then we moved on to another question. Here's some more answers actually. There you go. Lots of different answers and lots of perspectives. There's even more and whether there's a real distinction or not which is an interesting question too. Then we moved on. We're getting hot here. This is a theme that we adopted for the interest group. Actually Sarah shared with us these graphics. A lot of them are animated gifts which you won't get to see today. They're just static today but they were not fun. So here's another question which is, is there a difference between digital scholarship and digital humanities? Is there a difference and what would the difference be? So these are some of the answers there and then we asked another question and this one is about barriers. So what kind of barriers do people encounter when they're offering training support? And that's a question that was in my mind. Are we talking about people who are receiving the support or people are delivering the support? Are these questions and issues related to people receiving or the people delivering? People have different perspectives on that. So these are some answers people shared with us. All right. Next question there is imposter syndrome and this is a question that had the reason several times it arose at the skills summit. It arose last week when we organized another session at the e-research conference around how support and whether this is something that we need to address and how we would be able to address. Okay. Here's another question. What would be the most outrageous question you would need to ask? And these are some of the questions people posed there. So a few answers there and then this one is an open-ended one. We had a discussion about things you don't like about your job and then finally this one which which is interesting. So the story behind this slide is that a few months ago Sarah King came up to Brisbane and she delivered the training workshop at Griffith University and other conferences and she told me one of the issues that she encounters is that every time she organizes a training session the wrong kind of people show up. So she might be offering an introductory session and the people who are showing up are very skilled and they find it a bit of a waste of time for them. Or conversely it might be a session that requires a certain background and using technology and the people showing up were really lost and they couldn't keep up. And I suggested to her maybe every time she advertises a training session she could put in a spice index next to it. So mild is for people who would need an introduction and then medium to hot and spicy and spicy with people with advanced skills. So that's where this theme came up is should we have some gradation there. So I'm gonna stop sharing the application and get back to me and just go back to some of the provocations and some of the issues that came up from that session. So the first thing that comes to mind is what is it really about has that makes it different from the sciences and STEM in general. And one answer is that has is long tail. So it's not one single tool or one single application. It's many applications, many small communities using different approaches and each one of them are very different from each other. And this is a really big challenge for people supporting them as well as how we can offer the right support services and resources to them. Expectations vary a lot between disciplines. Some use quantitative methods and use qualitative methods. There's also a big distinction whether real or not between social sciences on one side and the humanities and arts on the other side. So we need to understand this nuance and find grain difference between the disciplines if we're able if you want to support them appropriately. The other question is what skills are we talking about? So skills to do what? I have to answer to that question. One of them is we need to think about skills for an individual versus skills for the community or towards the community. So for the individual, the skills we can talk about are skills related to gathering data, skills about creating new knowledge or skills about disseminating information using digital tools and digital methods. So which ones are we talking about that would be most interesting to the individual researcher? From a community point of view, we might think about skills related to the duty of the researcher towards the community. So are we talking about digital skills to ensure reproducibility of research? So that's one area of interest. Another one are digital skills to foster open research which goes beyond reproducibility into things like sharing data and licensing and so on. Or are we also talking about open scholarship which is not just doing research for the research community but also research that engages other communities outside of research so non-academic and non-technical communities. What kind of digital skills do we need to develop for these? So these are really interesting questions and another reason why this is really interesting is the nature of the change that is happening in the past disciplines. So technology is evolving all the time but the way the technology is being applied in humanities and social sciences disciplines is changing and evolving all the time. The kind of skill sets that humanities researchers have is changing because we have PhD students joining the cohort every year and these people might come in with established digital skills. So there's a lot of interest in this space not just by offering them support services but being able to keep up with this rapid rate of change and how we deal with that. So when we come back and talk about the digital skills we ask ourselves is this about developing the digital skills for the researchers themselves or is it about developing the research skills and digital skills of support staff? Is the purpose for the support staff to provide advice or to be able to do things? That's different kind of support that we're talking about. In terms of support staff educating versus training the researchers which ones of these are we meant to be doing? Are we meant to be modeling behavior or mentoring or none of the above? Are we meant to be conversant with digital tools or be able to be technicians and be involved and know how to ease these skills ourselves? So these are some of the issues that had the reason and these are some of the issues that research supports staff and the humanities encounter because there are so many tools so many skills that it's not reasonable to expect that one person be able to support all of these. So what is it exactly that we're able to offer and how is that distinct from what specialists can do a research software engineer for example and how is that distinct from what the research are meant to be doing themselves? One suggestion I had last week to the birds of feather session is that maybe we're talking about support staff that offer shortcuts so your real role is not to do things but enable researchers to find information quicker, have access to resources that they don't have they were not aware of or connect them to other people and that on its own is a very valuable contribution a support service. Moving on from the role of the individuals the other question was what is the role of the institutions in and there are two types of institutions on one side there are libraries and e-research support services on the other hand there are the schools the departments and the faculties is there a clear division and distinction between those roles are they meant to be working more closely there is a division of labor there libraries for example are they meant to be delivering new services do they need to skill up their staff or hire brand new types of staff that are not librarians is their role to simply troubleshoot and help people are stuck when they're carrying out their digital research are they meant to build some kind of relationship and then take those people through all of these stages from coming up with an idea all the way to delivering research outputs so that might might encourage libraries to think about coming up with a new way to offer these services and be engineer basically the workflow and how they engage with researchers going back to the schools what is the role of a school in this relationship are they simply clients for e-research support services and for libraries there are other issues that that the schools could look into for example cultural issues related to using digital research so one of the challenges with humanities and social sciences is that what often is quite departure quite a departure from traditional methods it is a different kind of epistemology than the traditional research that happens in the humanities out in social sciences it's quite often collaborative a lot of disciplines in the humanities are not used to collaborative research it's almost by definition interdisciplinary which means that you have to trust your partner who comes from a different discipline and has different expertise and also it's not part of the mainstream scholarship so traditionally people are meant to be producing conference papers journal articles and books and now we're talking about creating digital artifacts not traditional research output creating things like websites simulations games mobile apps and so on and how do we value this and this is where the schools could have a role to recognize some of these activities as a legitimate scholarship also recognize the outputs and be able to co-invest in them so this is really important to be represented as a strong voice and say this kind of way of carrying out research is a legitimate way and we need the right support from the university and from the support services another question that arose when we talk about the role of the school versus the scroll of libraries is is whether there's a division of labor there between generalist skills versus specialist skills so increasingly there are a number of skills that are needed across all domains i'm thinking about text analytics for example mapping visualization and so on but then there are also other very specialized tools for the discipline maybe that's one place where the schools need to take some carriage rather than the library are we talking about introductory sessions or something to work with advanced researchers on again what is what is the role of the library working with advanced researchers or is it simply for introductory material or is it somebody else's job so there are a lot of interesting questions there in terms of the role of the institution how they can support humanities digital research but also i think there is another role on a higher level which is the role of the academies the role of coal and other consortia about developing a national agenda for skills development for digital research support about integrating digital tools and methods training into research training which is not happening just yet so we want to build that pipeline so that people who get their PhDs are already skilled and digitally ready to carry out digital research rather than starting from scratch one other issue that we had is is about people are already in academia who need to skill up and they don't have opportunities there to do so so we want to develop pathways for professional development for academics so that they can develop their digital skills so a lot of interesting questions that had arisen i don't think there's one single answer but i think by working together there might be opportunities there to come up with some really interesting initiatives that are both for individuals at the level of the institution and on the national scale so that's pretty much it and what we talked about thank you very much thank you very much for that Marco lots of interesting questions okay so next up this i'm very happy to introduce Professor Michael Hall and Dr Martin Schweinberger they are both from the School of Languages and Cultures at the University of Queensland Michael is Professor of Linguistics and Head of School and Martin is a postdoc research fellow and they will be discussing their language technology and data analysis laboratory over to you okay so um as it happens i think our presentation talk follows on very nicely from the one Marco I gave and raising the questions around that balance between general support for digital humanities research and digital methods and humanities and what it is we're doing in the school where we're trying to provide more specialist support okay um so this this is just introducing us we've already been introduced I think just getting used to Martin's mouse um so I guess starting off just to give the bigger picture of where we see the sitting essentially the world economy is changing and the world's economy is shifting to an environment to which data is really part of the economy and we can start talking about the data economy and if you start looking at some of the big companies um uh in the world I'm just showing them here what you find is text analytics lie at the core of some of the biggest companies in the world and I think research and teaching the humanities there's growing awareness of this but there's a real pressing need for us in the humanities to be upskilling so that we and the research we're doing we're taking advantage of all these computational opportunities there are but also that we're passing on these skills to our students as well so what what we would agree I think here is that there's an enormous potential for bringing in community computing into the humanities there's opportunities around big data which really until this point in time where we haven't had but there are now mega mega corpora you might say and probably the best example of this in Australia is Trove which was um held by the national library um the the Australian web archive which is part of that is 20 years of the Australian web um we talk about that I think it's 600 terabytes or something of that size but it's really massive um and so that requires uh both computational infrastructure and also computational skills which are really new to the vast majority of humanities researchers there's also the possibility humanities is possibly a little unique compared to other areas the data that comes into the square mile astronomy array is really only usable by astronomers however humanities data is is almost infinitely reusable and that that creates a lot of opportunities but also requires skills being able to transform those data sets use them in different ways for different different purposes as well and it's really interesting real-world applications as well um so given this kind of araman as as I've said there's really a pressing need for training and education in computational approaches and digital tools in the humanities make sure that we're keeping pace with other fields of scientific endeavor and also for Australian humanities remain internationally competitive and also students themselves increasingly demanding these kind of skills and the courses they do um when we start looking at it you can see the picture um you know the reality is there's some real local challenges in dealing with this there's issues around ensuring best practice and transparency and research that we're we're providing access and sharing of data this this real strong movements with the open science movement has had a real impact on the way in which linguists are working and so that that's certainly this movement there however there's still arguably some kind of reliance perhaps over reliance on existing tools sometimes their commercial tools and what that means is the research process if you move across to commercial tools the research process actually becomes more opaque and that's not really what we're aiming for in the science world um of course we're dealing with people um who are used to doing research in certain ways and some of them um are they willing to change there's different needs across different disciplines there's different levels of experience and expectations and also there's just a lack of really sort of specialist material and training so the approach we've taken here in the faculty is to pilot an approach in a particular school and then move to to sort of spread that out across other schools in the faculty and the approach we have is a continuum between generic training which is as Marco indicated something that the library can pick up and and they're providing introductory courses and more general courses and we work closely with our library liaison officer to make sure that we're complimenting what they offer and what we're doing in our school is more specialized training that really fits the needs and if you're going to get staff on board then being able to pick up at the point they are at in terms of their own research programs is really important rather than here's some general stuff you might think about but in doing this particular research project what is it that you you can be doing so in order to meet that need we've set up our own online virtual lab which also has a person at the moment it's Martin who's working really closely with staff and also our PhD students in the school so I'll let Martin take over here right so I'll talk about what we've done and the visions we have for the language technology and data analysis lab LADAL which is essentially a support infrastructure for people who are interested in computing and digital aspects of house in our school it specifically targets tremendous researchers and it basically is there to enhance and complement existing our programs there's not entirely new but it basically fills gaps that where they're basically expensive them and by basically offering these services we hope that we can offer new pathways into new research possibilities so how to basically look at data a little differently and maybe tease out findings that we will not be able to find before and essentially the LADAL has two components to so there's a real physical space that we're in the process of setting up which is a specialized computing lab for language based computation and experimental work so there people can can be recorded during conversations or for example acoustic analysis can be done there and then we have something which is still work in progress but we have a test site there which is an online virtual lab which is the LADAL website where we have basically tutorials and explanations about methods and stats which basically guides someone who's interested in that just through how to do stuff in a step-by-step fashion so when we look at the services that I offer at the moment and I hope that I'll have more support in the future is basically offer training and workshops about computational digital research methods and technologies also to basically provide information and self-guided study materials because basically from my experience I can say a lot of the questions that I get and the issues that researchers in the school face are kind of similar and we basically create these materials so that I can basically point them to that and they can basically discover how to use something by themselves that basically reduces my workload and also is more efficient just in terms of how researchers themselves can skill up and also I give hands-on practical tutorials and workshops where I introduce digital tools or computational methods for data extraction and processing how to visualize data or also stats which is very popular in the school and the idea is basically to teach people how to code without basically teaching programming per se but basically how to use a computer to create graphs and they'll pick up language just like children acquire a language in the first language acquisition and additional feature is that which is very important that I offer face-to-face consultation so for example researchers come to me and they have this data set and then they basically just want to figure out okay what can I do with it and what do I have to pay attention to when I when I gather data but also analyze data right um so the aims that we have with this lab is to basically create skills in the school to basically enable researchers to skill up their own research methods to develop themselves when it comes to digital tools and data management but also when it comes to computational methods and very basic program programming skills in the end where I would like to take the lab is where we really have where we really enable people to do data extraction transformation processing and analyses in a very transparent and replicable way and that also allows the researchers to visualize data including geospatial data so mapping but also creating interactive web apps in a very sophisticated sophisticated way and as we're in the school of languages and cultures focuses of course on natural language processing applications so text analyses and statistical procedures including also classification and machine learning to a certain extent right here just some examples from the tutorials that are there at the moment which basically focus on different types of computational analyses and how you can visualize data so just basically to show you the range of things that we offer so we have network analyses just violin plots, wood clouds, very sophisticated and new statistical procedures so the box plots there represent a Baruta analysis the world map that you see is also created by by some apps that we use and we have conditional inference trees we have specialized visualizations for liquor data and also mosaic plots if you have contingency tables I want to visualize them so basically the idea is to train people in you know how can I create these nice graphs and basically um showing my data in you in interesting ways right okay so just just to summarize um how's our pilot gone I mentioned this is a pilot we've launched in our school with the view to seeing how it's extended across our faculty um I would say it's an outstanding success um I can say a lot for Martin um and I think one of the measures of it is really the demand from humanities researchers in our school really exceeds Martin's ability to work with them um so we're looking to extend the number of positions we have both in the school and across the faculty um it becomes really clear that we need a range of roles fill out in this area ranging from lectures postdocs through to social and cultural data scientists through to platform software engineers who are used to working with humanities people um and we see data scientists in the lecturers as people who can play a key mediating role between platform software engineers who obviously have specialist skills and researchers who obviously not going to be familiar with a lot of the terminology that is second hand to people working in this computational area and a lesson is it is possible um but we need to work hard to make sure that we're communicating all the time with the library uh with the research computing center uh with with the staff to make sure that we're aligning what we're doing um but I think the future is bright and uh we're really happy to share what we've we've discovered here in the school with others around the country thank you great thank you very much for that Michael and Martin uh now um next up I would like to introduce my colleague uh introduced my colleague Alexis Tindall uh Alexis is a senior research data specialist at the ARDC and is currently spending a lot of her time on the HASRDC project uh so Alexis could you please give us an update on how that's going thank you Matias um and this is going to be a brief presentation because it will be a short update on this project it isn't strictly speaking a product of the skills summit which is the goal of the other presentations in today's uh in today's webinar um but we thought it was a unique opportunity to connect with a group of participants um and attendees who are interested in humanities arts and social sciences um and so an opportunity to update on a project that the ARDC is working on um that is relevant to that community so thanks for joining us um I'm just going to give a little bit of background um as many of you may know in the 2016 national research infrastructure roadmap um the uh that review of research infrastructure investment um which happens periodically called for further investment in platforms to humanities arts and social sciences and also for investment in um environments for analysis of indigenous research data as well um that since that 2016 roadmap came out there's been various twoing and throwing between the community and government on that um and the government the department of education has been making an effort to um to get further input in 2019 they announced a national research infrastructure scoping study which is usually a process that precedes research infrastructure investment um and in order to help gather information for that scoping study they've commissioned a couple of pieces of what we're sort of calling pre-scoping work um which will be carried out um by the Academy of Humanities the ARDC and a private group called dandelion partners um these are complementary pieces of work and the Academy of Humanities has just is just coming to the end of a piece of work looking at um international exemplars of research infrastructure support for humanities arts and social sciences researchers um and the ARDC has been charged with looking investigating the opportunities and the environment in which we might talk about humanities arts and social sciences research data commons um just a bit of background information what is a research data commons some people on this webinar will be very familiar with what i'm talking about but just in case um and also research data commons is the term for cluster of activities that is delivered in varying degrees for different disciplines depending on the needs of those disciplines from the ARDC's perspective a digital research data commons brings together data and related resources to enable researchers to conduct and collaborate on world-class data intensive research as well as enabling access to data and methods of sharing a commons can include computing resources and analytical tools and working environments storage models methods for sharing um for sharing methodologies and other kinds of support um the nature of a hash research data commons will depend on the priorities and needs of the communities with which ARDC connects over the course of this project but the ARDC also would like to mention that um a common solution for this or any community also involves cultural and social solutions as well as technical solutions so policy governance training and skills complement and enable world-class research environments um what are we looking at in this project according looking in our project proposal we're looking at the fact that a hash research data commons if we if we take it at the simplest level in that natural research infrastructure roadmap they talked about platforms for hash um this is taking a bit of a deeper investigation on that and saying look if there was a hash research data commons it may not be one solution for the entirety of the hash community um but it may be made up of a developing coherent environment of connected commons that address the needs of individual research communities or clustered research communities determining on those determining uh depending on their priorities part of our project is to identify and group research communities with similar priorities and needs in this area um we're looking at mapping nationally significant hash relevant data collections identifying opportunities to leverage and enhance existing initiatives and identifying gaps in discoverability accessible and interoperability for existing data commons like activity what does this landscape look like well it's we're sometimes mistaken when we say there hasn't been research infrastructure investment in hand has there has been but it's dispersed and uncoordinated and maximizing the value of that research infrastructure can be benefited uh uh great benefit can be realised for the community by being a bit more coordinated in the activity so we're looking at existing investments and you can see a couple of them in this sort of loose group of balloons here ARC projects leaf funded projects the galleries libraries and archives museum sector institutional programs um like martin and michael's government data the work the ARDC has done previously and that kind of thing um so it's a it's a broad landscape we're talking about there is a lot of activity in this area already and what we're talking about here is perhaps looking at how we can ensure those efforts are coordinated to ensure the best value for the research communities um how are we consulting on this project um we've got a few avenues of consultation that are happening simultaneously we're reaching out individually to major data platforms in this environment so has relevant data platforms and providers um we're working with the academy of humanities the and the academy of social sciences and our dj partners through arnett and the the other dj partners um we're looking we're holding a researcher consultation at the upcoming Australian Academy of Humanities symposium that's happening in bristol in november we're looking over the the f or codes that are covered in this area and reaching out to researchers within disciplines that we haven't covered to the other means i'm working on a broad reference group so some of you who are on this webinar i may have already spoken to about this and others you may be on my list already of people i'd like to speak to about this in that in the second stage of the project when we're talking about throwing up models and proposal i'd really like a very broad reference group to offer us critique on that um and it's uh these projects are uh are not strictly related but um as many of you may be aware in the last six months the ardc has um supported a range of data and services focused discovery activities and he's also presently in the process of calling for applications for platforms funding um those applications closed on friday and the information that has come out of those processes has also been a good pointer to existing activity in the area and we're also doing individual reaching out to researchers um in areas that that aren't covered in those in those by those means um the timeline for this project is roughly described here but it is a little open we're talking about information gathering for the remainder of 2019 and during the early three months of 2020 looking at developing and consultate consulting on possible ideas for what it has to research down with comments would look like and the other information we're providing to the Department of Education we're looking at delivering a um a final version of this information around march but we do have the project officially runs through till the end of financial year so that gives us an opportunity to review the department's um in areas of interest the reaction and the community's reaction to the proposals being developed and talk about how we can continue to be involved in the scoping study work that the Department of Education is talking about this is a multi-stage process and at this stage this is an information gathering process or only um after this the Department of Education will conduct their own scoping study and um it remains to be seen exactly what that looks like but we're pretty optimistic that it might lead to some research infrastructure investment so what is it starting to look like um this is a very hastily thrown together and a map of the kind of things that are emerging or the the landscape that we're looking at here down the center of this diagram we can see a number of research communities that we're connecting with and that are that are data users and that have particular data needs or relationships with data platforms and providers we're looking at existing um data providers in this environment you can see many of those that you'd be familiar with um on the right hand side of your screen there um notably I just point out you know I've got a large box there for GLAM which is oh which is um covering a large number of institutions but I've also specifically drawn out Trove the Trove Australian Web Archive and State Libraries Records and Archives projects as well um you remembering my slide with the balloons the ARC funded project the leaf funded project the institutionally supported projects each of these data providers um existed a different administrative environment and a different funding and sustainability environment and that's an interesting challenge to overcome there as well we're also looking at related initiatives that could be leveraged and enhanced as part of those projects and some of them are pictured there on the left hand side of your screen um these are projects that are presently funded by the National Collaborative Research from Construction Scream and others um activities by government activities um even the ARDC activities um and uh and other uh related initiatives that are there what uh the other thing I just wanted to briefly go over is what what sort of issues are emerging if I know that some of you have seen me talk about the background to project before um look I'm just going to flag a few things because this is very much an unsorted and unprioritized list of emerging issues right at the moment um but just the things that are coming up are things that may be familiar to many of you who work in this space already but it's good to have these things documented and described and examined in a way of how they might fit into research infrastructure support so issues that are emerging as we consult with these communities are the longevity sustainability and access to data that comes out of ARC funded projects um whether that can be reused whether that should be reused whether um old data can be accessed again the challenges of accessing data the data level when it comes to collections of past data versus metadata level access um the challenges of sharing qualitative data versus quantitative data um the use of consistent metadata in different research communities and um how confident and confident they are in using metadata whether the metadata structures that exist are relevant are working for them um the need for secure analysis environments for sensitive data this is something that's happening in various ways across this research landscape and that's worth looking at as part of this project community access to data about themselves in many cases humanities arts and social sciences research is research about people and there are a couple of different applications where it's particularly important to ensure that those people have continuing access to the data that has been collected as part of research about them the challenges of accessing government data um that is administrative data survey data sensitive data and in some cases even the cost of accessing that data as well um another thing that's come up has been about um platforms for sharing um non text based data so 3d uh 3d representations and things like that these are just a very loose and um a loose the loose list of things that are starting to come out as we talk to these research communities it needs a lot of digestion processing and prioritizing at this stage so don't take it as we'll be acting on these things specifically but it's just to give you an indication of what's coming out of conversations we're having in this environment um additional perspectives that we have to continue consider as part of this project is what is and should be a national responsibility and what should be an institutional responsibility and we've also been asked to look at criteria to determine significance for has data of national significance so the question that you may be wondering is how can I be involved there may be something that you's leaping out at you that should be a part of this project and there's a few ways we're holding this consultation at the Academy of Humanities Symposium in Brisbane in the 15th on the 15th of November um that consultation is invitation only but it's not exclusive we are trying to focus on researchers as part of that consultation because there are other opportunities to connect with the research community research support community um I as I mentioned I'm building a emerging reference group and I would love more people to be in to express interest in being involved in that I am connecting directly with researchers groups of researchers or data providers and so I'm able to video conference or meet with people as relevant if there's insight that they need to share um you should watch the upcoming ARDC newsletters and we will have a project page on the ARDC website soon as soon as I get uh some time at my computer to ensure that that's appropriately informed and I would encourage you to contact me so I'll just finish by sharing my contact details here um I'm very happy to talk to anybody about this project I'm also particularly happy if anyone has um an area that could benefit from this project that they'd like to highlight to me great thank you very much for that uh Lexus uh and now we've come to question time so I'd like to invite all the panelists to turn on their webcams and unmute their microphones um now we already have one question how many digital skills should be embedded within core units considering digital tools such as text analytics spatial analysis and so on enable new interpretations due to the nature of computation should they start to become digital research methods maybe I can have a stab at this one first uh so this is an issue that came up at the University of Queensland which is what is the baseline uh skill set useful skill set that we need to impart to our research students in general uh and it's really hard to say because it varies from one domain to another some some domains have that integrated already as part of the research methods courses courses while others uh just let students do whatever they want to do uh one thing we've done at the University of Queensland is we set up a fellowship program called the Graduate Digital Research Fellowship and the fellowship is for a great um confirmed PhD students to spend a year to develop a digital artifact and in the process they're going to develop a digital skill related to that and that digital artifact will feed into their dissertation uh difference is that that fellow will be part of a cohort of other fellows who were chosen to carry out different digital research projects so each fellow will have its own method and by those fellows getting together and meeting once a week then they inform each other of progress and they'll learn about some of the opportunities and challenges that each method are thoughts so by the end of the fellowship not only would have gained the skill in one particular method but you become conversant in other methods uh that works really well if we selected the right fellows and the right mix of methods and disciplines so that's how we we we uh we address the issue by by having this mixed cohort and then by by working with them over our whole period of year rather than introducing one topic over a couple of hours which won't cover anything thank you Marco Michael Martin did you have anything to add to that I have ideas but they might not be that popular um so I love unpopular ideas well um it would really help if we if you might introduce basic programming skills um to the young researchers or PhD students um or even BO students uh because instead of basically learning new tools and basically at the end of your PhD you've used 20 tools or something like that you learn one programming language and basically then it's very very easy to adapt different packages that's very simple but I also have to agree with Marco wholeheartedly because I know the fellows and the diversity of projects that they that they do and so basically for them it's actually very good focused on very different things and to be honest I wouldn't know how to do many of the things they do in Python or in R but you still need very specialized tools to to get the job done but ideally I think it would be perfect if if young researchers or students would get or learn a basic understanding of of very basic programming skills and there doesn't matter whether it's Python or R or Java doesn't matter um I think my radical opinion as well um since I'm walking in front of the humanities faculty right now um I would say yes it really needs to be at all all levels and yes at the research level if you actually at all can do really specialized I mean we talk about undergraduate students yeah we need to really start seriously thinking about the humanities programs how we've fed those and to introduce computational thinking for the students because we've seen the data economy the data economy revolves a lot around text and humanity students and images film and so on so these are things that humanity students are dealing with all the time and the interpretation of complexity of those interpretations um and it strikes me that there's really great opportunities for students who have these skills to take things forward in the new economy so this is a little radical though for humanities faculties I think so it's a step by step process okay great thanks for that now I I suppose actually I have a question um slightly personally uh motivated so I come from a um librarianship background while I studied computer science as an undergraduate and I've spent 15 years as a librarian but I have practically zero experience in actually undertaking research uh so short of doing an MFIL or a PhD or something like that uh how can research support professionals like me gain a deeper understanding of the methods used in some of these disciplines that don't necessarily uh well that we don't have that much experience in I think this is we're looking for new positions in universities and you see them in institutes which are larger so the medical institutes and so on they have what are called research data scientists um and I think research data scientists are in an ideal position to help explain to to people in the professional roles what it is researchers are doing without getting low because if you go straight to the researcher they'll give you the trees right I mean you won't get the bigger picture um so they'll help to give you the bigger picture and also help connect and with those researchers I think people are nice kind of roles um and I consider martins in a research data scientist role um the thing about the research data scientist role is universities haven't figured out is this an academic position is it a professional position is it a combination I think different universities are coming up with different answers to that question um a martin I should say for him he's in an academic role um so his role is academic but he's like an academic data scientist you could also have more of a professional data scientist um but I think people are nice kinds of roles and if you're got a background like yours you know that's that's a great role to get into um I think you cannot overestimate the importance of being able to communicate between between different groups because it's really about translation in a way so um the mere fact that you know what people mean who come from computational point of view and to be able to communicate that is is very important and we need more people who are in between who are mitigators mediators between between those fields because very often when I talk to researchers they they don't really know how to translate what they want into a language that would be understood by a computer scientist and then both sides are frustrated very very quickly because the computer scientists will end up working endlessly because it's not clear what he's supposed to do or she's supposed to do and the researcher is not satisfied because um the researcher doesn't get what he wants you know so I think the the ability to basically translate is is very important and cannot really cannot be overestimated okay great now well we do have a few more questions from the attendees so um so uh what are some strategies to start introducing digital study to reticent humanities schools uh so if I may take a a step at this one so when I first joined the University of Queensland I was I was asked to go and support the fact of humanities in the university and that's about a thousand people between academics research students and so on and the problem was there's a lot a lot of people didn't understand what it is to do digital humanities and whether that's something different from what they're doing or there's something they're really doing uh so the problem the the challenge I said to myself was to educate those people at the first instance once they recognize the value of using digital methods and digital tools and we can train them but if you just train people without explaining to them what they're getting trained on then you're never really going to get any research value out of it so we set up a number of engagement programs to educate people by showing them examples of other researchers and other universities and other disciplines and how they use digital tools and inspiring them with that and saying wouldn't you like to do something like this and that starts a conversation well how how do I get trained where do I get the resources who are my collaborators and so on the other aspect of it is to normalize the practice of digital research and the humanities and social sciences so one of the issues I encountered when I uh is I interviewed a lot of researchers and PhD students and they told us that they would like to carry out this kind of research but it is different from the mainstream it's other and that is a big challenge because it doesn't get recognized and all of the investment they make in training and skilling themselves up and building digital platforms and tools and so on wasn't really treated as legitimate research so one activity is that we are undertaking is to normalize digital research and accept it as something that people from any discipline could engage in regards to what the discipline is and what the method is so we had an engagement public engagement program where every semester we had an event we showcased examples of technology that is being used to develop at the university and how it's been applied across the humanities and social sciences disciplines and that's to value and recognize those people working on it but also for others who don't to acknowledge its existence and acknowledge that the university accepts that the legitimate scholarship so it was both a skilling program in terms of education and training but also inviting others who don't engage in digital research to accept that kind of practice and make it part of the mainstream okay great thanks Marco now we only have a couple of minutes left um there are a couple more questions but we'll quickly switch track to you Alexis uh where can we track progress on the commons will it be ARDC website focused or social media oh gosh um and so that's the ARDC website at the moment it's difficult to find any information but largely because I haven't filled out the project template to get the page up on the ARDC website yes I've been too busy running around talking to the community yes we will have a page on the ARDC website it'll be in the form that we do our project pages on the ARDC website which is a timeline-based form so a bit of background information and a timeline going down the right hand side that should give you an indication of where we're up to in that timeline any outputs from the project that are a good remade public should be shared in that environment but I cannot make I'm not 100% sure what they're going to look like just yet as we make announcements on our progress through that timeline the ARDC newsletter is a good place to get that information from personally I'm not a big social media user um but you might want to follow the ARDC Twitter which we use to complement our ARDC newsletter for major announcements of that kind as well so I think the answer is everywhere but um ARDC channels will be the best place to get that input can I can I slip in here and just plug in the house virtual lab so we have a suite of tools called the tinker suite we have the tinker studio but also we have social media presence we have a facebook page where we post stories about digital tools and research methods being used but also information about what's going on in Australia we also have a newsletter that you can sign up to so visit the website tinker.edu.au and you can sign up for the website and for the newsletter and we're working on pushing a newsletter that is specifically targeted to digital research support staff and that's coming up very soon we're working on it at the moment. Okay great thank you for that now with one minute to go there's one last question so I beg your forbearance um so how have computations tools been disseminated within the humanities so so how has that happened until now in one minute um by basically um people leading the way I mean I come from a corpus linguistic background and um people were interested in basically you know how can we empirically test our ideas by language and then it came very naturally that people became more interested in statistics just look at how often statistics were mentioned in general populations they're basically increased exponentially uh since the 2000s yeah and so it just became more prevalent when people were more interested and they skilled up individually um and now we're in corpus linguistics actually quite quite good in that respect right um but I think we need to professionalize that not only basically make researchers skill up independently but really to be more efficient and set up an infrastructure problem. All right I muted myself uh we'll probably leave it at there but I would just like to very quickly share the details of our next of the last webinar in this series uh digital skills training in ecology and bioinformatics that will be taking place on Tuesday the 19th of November and you can sign up for that at the ARDC events page. Other than that thank you very much for coming I hope you all enjoyed yourself and I'd like to thank our panelists one last time Michael, Martin, Marco and Alexis and please have a good day