 Okay, everyone can see me now and welcome everyone, I'm Hans Kraus from the Australian National University. I can see we've got about 20 people on this, how interesting, I've never done this before. Okay, well I'm here now today to talk to you a little bit about the ANU data management workshop that we've been running for a few years now and it's run by the Information Literacy Program here at the ANU. I'd like to talk to you a little bit first about the ANU Information Literacy Program, ILP. We are here to support ANU students and staff in the development of computer skills and information skills. And this is done, we do this through generic and course embedded training sessions, also through one-on-one help for research students and staff that at times gets quite busy. And online tutorials, guides and help sheets, we are very much involved ongoing in developing more material. Of course fairly slowly because we're a fairly small group of four people working here. Okay, so the ANU data management workshop that I'll be talking about for most of the time today and here's a little overview, what the objectives are of the course, talk a little bit about the workshop itself, about the content and so on, manual, I should talk to you about the manual that we use in the data management plan, also how we publicize our course and the kinds of comments we receive after running these courses. Okay, so the objectives really of the course are that the attendees, mostly they are mostly research students, they understand what research data actually is and why it needs to be managed. Also for them to appreciate any legal, institutional and funding issues relating to the data they're working with, of course data in a very broad sense. And also to learn how various data management methods can help them to work more effectively with the data. And also of course very importantly develop an awareness of existing data management services at the university where they're studying. Also in many cases we don't have the time really and at that point not really the need to go in depth with any of this, it just needs to be understood largely as an overview and an introduction to the issues involved with data management. So the workshop, we've had it now since 2008 which is when originally a PhD research students in the Department of Computer Science compiled it put together. Since then we've given it a number of revisions because things have changed, we found due to feedback from the students, other ways of approaching some of the material, we've made some changes. We are not running a great number of them at this point only about three to four workshops every semester. So you can see here a little diagram of how the course attendances have developed over the years. So 2008, 2009 until 2012 you can see the different years and what was different colors and also the average number of attendees is not that huge. We even have had ones when we only had two attendees come in. We've had up to nearly 20 in some of the courses. Feedback is very positive and appreciative and it often turns out that the students who come had often not been aware of the issues involved and what sort of basic tools they might have available to them in order to manage their digital data. When it comes to the content of the course, just this is a little overview here of what we actually go through when we run the course. We talk a bit about bibliography management. The ANU has a free version of the NNOT bibliography manager and database available to all members of the ANU. So this can be downloaded. So we of course also run separate courses in NNOT, teach the students how to use NNOT. We also cover and touch on file transfer issues and remote access to the various places where digital data files can be stored at the ANU. We talk touch a little bit on file synchronization, talk about revision control, manual methods, automated methods and so forth and also on make a few suggestions on how collaboration between members of the research group can be managed. Often here the local settings in different parts of the universities vary quite greatly from other areas and in many cases if anyone wants to pursue this further they will have to be referred and we do actually refer them to their local IT support staff. Every college has several of them. Very much we also talk about backups. It's often interesting to see how we kind of expect that anyone would intuitively create a lot of these backups or is familiar with synchronization and version control issues. It's often interesting to discover how still there's a number of students who come to these courses who have no set procedures to handle these. Security of course as well, IT security. We also at the ANU make available free virus software which people can download and use on their own computers, laptops as well. So we talk about that as well. The awareness of that even though it's widely publicized is often not there. I can't assume that everyone knows about this. We also talk about the space on the Pebble server. Pebble is the ANU white file server so every student, every staff member has space on that which can be accessed from campus and from home as well. Many students who come are not aware of that. They're not aware that they do have file space on the Pebble server and many even more are not aware that this can be accessed from home or from outside the university. Then we have a collaboration software that everyone has access to. We call this Alliance. It's based on the open source software which has been developed by the Sakai project. Many universities of course and other tertiary or educational institutions use Sakai as a learning management system. We have installed it here on campus as a collaboration option with file space and other ways to collaborate between people across the whole world. Also we talk in the course about ANU digital collections which is the ANU's online occasion for collecting, maintaining and disseminating the scholarly output of the university and the supercomputer facility and others. Again at this point I'd like to say that usually there's not enough time really to go into any depth with this but still we provide information on what to do next if people need to find out about these things. So really very much so in this course we provide information sharing and awareness creation exercise for students. The next thing benefits and especially requirements of data management are issues which many attendees are unfamiliar with. That's always interesting to find out about and we raise awareness for relevant documents like the ANU responsible practice of research policy, the Australian Code for the Responsible Conduct of Research and the ARC funding agreement for discovery projects. So we provide them with methods to access these so they can study them. Of course we don't have time to talk in depth about this. So the manual, our data management manual is openly accessible to everyone. There is a lengthy link, don't bother writing this down, I'm not sure whether I assume that this presentation will be, of course it will be available online, we will see the slides as well but if you want to quickly just write this down, especially the quick link here, quicklink.anu.edu.au slash zaslowercase98 will take you directly to the manual. Data management plan which is not generally part of the workshop any longer except where participants requested, a template RDF file is available from the above site. It's very basic, just two pages of some issues to be considered and then some space underneath for people to enter their own plan or procedures. Okay, how do we publicize it? It seems that because of the low number of people who come to this, is this not considered as something necessary, do people maybe find out the information from elsewhere. We do publicize it widely. The information literacy program publishes every year a LearnHow booklet which gets distributed to many locations across campus, libraries, halls of residence, computer labs, lectures often hand the booklets out themselves in their courses. You can see an online version of that, again lengthy link, quicklink, again forward slash HZEP will take you there and you can have a look at it. It lists all student training and support services which are available at the university that enable the development of data and other information literacy skills. We run quite a few courses throughout the year. Here's a little double page spread from the booklet shows the data management entry, brief information on this and then a way to access the online registration page where they can see the dates when the workshop is run and they can register. We also can see that they're utilized in many cases QR codes to make it hopefully easier for students to register and for more to come. The other methods we have a well-known website where training courses, workshops are listed. These are not academic courses, these are just training activities that happen ongoing here at the university, the site address is training.au.edu.au, of course anyone can have a look there and you will find our courses there as well. The data management course in some cases also is requested for small groups of research students, for instance the Fenner School Honours students, convener regularly requests for us to run the course for the students there. We also have an ANU library Facebook page where we advertise the course and a few other methods to reach out and inform potential participants about the course. Comments we receive, not too many, we have an online feedback form where people can provide some feedback, it's really throughout all of the workshops it's been very positive, here are some of them and what the benefits might be that people gain from attending this course. Again you can see there remote access to people, that's one thing that people comment on that they didn't know about Alliance, that's also not very commonly known, we run courses in Alliance and how to use it. And of course the last one there under that first question is what is data management about, it's usefulness and how to use it. It was good and these RP programs are really useful, please continue them, even in future for the benefit of students, okay and that's thank you and that's my thank you as well. Here are my details, if anyone wants to get in touch with me, I'd love to hear from you and I thank you and I can pass back to Jerry. So thank you Hans Jörg for a very useful and interesting presentation, we'll hand over now to Rebecca Parker, so I'll just switch controls over to Rebecca, so you should be right to go Rebecca. Okay thanks Jerry. Excellent we can hear you. Thanks very much Hans Jörg, it's kind of hard to follow your presentation about such very clear practical training in data management with what I'm about to talk about. We are at a point at Swinburne and we were when we did this particular session where we had a research repository and the ability to describe and promote data sets and send them to Research Data Australia, but we didn't have data storage and we only had a draft data management policy. It's actually very difficult to enforce a data management policy without data storage and it's hard to encourage good data management practices without a policy. So part of the purpose of this session was to discuss with researchers what they would like the policy to look like, what would be practical for them. So the three presenters were me, I'm the Research Services Librarian at Swinburne so I look after all of the services that we provide to researchers from the research repository for publications through your data, copyright advice, all those kinds of things. We also had Terence Bennett who is technically employed by the College of New Jersey in the US but he was on succumbent to us as a Research Data Librarian and we also had Sonia Peddle, a research fellow from the Swinburne Faculty of ICT and the Dean was present as well. The first thing I'd like to point out is that the reason I've been asked to speak to you today is the difference in our presentation that we had a researcher talking with us as well. But Sonia is a researcher with a research interest in data management and policy modeling. So I wouldn't say that the kind of presentation that we did would work with every researcher or any researcher. Sonia's research is also really multidisciplinary so she was able to give examples right through from anthropology to computer science to quite hardcore data and that meant that everyone there was covered no matter which discipline they came from. The reason I want to talk about this style of presentation is that I think researchers opened up far more because we had a researcher stand up and honestly say this is really hard to do and far from perfect. From experience when I've encouraged researchers to openly evaluate library research services like the repository, they've been really reticent to criticise anything in front of me in case they hurt my feelings and they probably would if they said anything really mean. But having Sonia facilitating the discussion definitely made a difference to getting people to open up and making it more interactive. This is just a quick discussion about what an agent-based modeler does just in case not everyone knows. What they like to do is they like to model systems and how people interact with them and how policies grow around systems and how these three things interact. The significance of the way that we ran our training workshop slash sessions slash free for all at Swinburne is that it was a workshop not training as we know it. We probably asked more questions than we answered because we didn't have the storage and the policy and everything to point to and say this is how you've got to go about it. We just wanted people to start thinking about how they would look after their research data. We were enabling discussion but probably not really dominating it. We also went with the approach of facilitating rather than leading. So this was a user-centered discussion about benefits. The purpose was, as I mentioned before, to receive input about how we might design a data policy that suited researchers. I think it's unusual perhaps for researchers to contribute to how we think about data policy. I think a lot of that sort of thing is worked out by support areas like the library and IT and research and maybe even the intellectual property office. But it was a great opportunity to say if we designed a data management policy that you needed to comply to, how would you like it to look? So we asked researchers to think a lot about the big questions. We're still right back at that point and to tell us what was getting in their way. It was a two-hour workshop with cupcakes, which was probably the most popular part. I've included a few slides in this presentation that came from our training session so you can see the kinds of things that we discussed with researchers. So we discussed the value of data management in terms of sharing. So sharing with yourself in the future, as Ann's likes to put it, or sharing with another. We also talked about how we can promote research through the repository because that was something we were actively, practically able to do at the time. We asked this question of researchers and a lot of them looked a little bit guilty. When did you last see a computer with a floppy disk drive? Well, I haven't got one. And I was willing to stand up and say, and I've got stuff that's sitting on a floppy disk drive that I'll probably never be able to retrieve. And I think that relaxed people a bit. The value of having a researcher in the room was that we could actually give some real world concrete examples of what data looks like and how we might need to manage it and what the differences between kinds of data are for access and ownership and even the ability to share. So this was one of Sonya's slides about the kinds of data she had collected through one of her projects. So it was everything from quite rudimentary things like the BARC reports that have to go in with the project and keeping an eye on the budget and that sort of thing right down to analyze data, photographs which could never be shared because they were children, server log files which nobody feels particularly sad about if they are public, but just the breadth of the kinds of different data really opened people's eyes a little bit to what it was that we were thinking about when we talked about research data. We didn't specify who the audience should be. We talked when we promoted the event about getting people along who were interested in data management policy and how we might go about developing one. But we did get lots of HDR students, lots of PhD candidates and lots of early career researchers. The project officer in the research office who at the time was drafting the data management policy also came along which was really good because she could be there and hear in person what people's pain points were. But because of the audience that we attracted we decided to choose to focus on promoting data as early in your career we went with the idea that all promotion is good promotion and the ability to promote your research through sharing your research data has to be beneficial and that seemed to work quite well with people. We asked them if they were sharing their data and how they were sharing their data and what we could do to make it easier for them to share their data and we did find out that there are quite a lot of wounds quite close to the surface which was a little bit of a shock for us. We knew it wasn't easy but we didn't know quite as much detail as we found out from this workshop. We didn't for example know about some of the competing interests at work so we realized that there's a really vast literature on data sharing and the impediments to that particularly in certain disciplines but we hadn't thought so much about what the relationship between sharing data and accessing data is. So when we sat down and said why would you share your data how would you share your data some of the questions we got were I can't access the data I want why would I share my data and they gave quite concrete examples of data sets that were held at other universities and actively not shared with them either by email or through a repository and that was a discussion that was quite hard to move past. They weren't making a distinction between accessing data including paid data and sharing their own it was all part of the continuum to them which was interesting because it's not really the way that our experience with making research data sets available through ANS had told us. Data was also seen as a commodity by many especially the engineering researchers who were present so they were interested in commercial data that they either couldn't get access to as mentioned before or was worth tens of thousands of dollars and they wanted to know why they would share their data freely if it was clearly of some monetary value to them. We were also perhaps not quite as aware as we are now of the issue of commercial and confidence data so we realised because I come from a publication's repository background I've got that perspective already but we realised that one of the reasons that we sometimes have to embargo these is that there's confidential material in there that can't be shared because it could identify someone but it never occurred to us that there's research that some of our academics are working on right now with industry that they can't even let their competitors know they're doing let alone sharing the data that's an outcome of that and that was an eye-opening experience for us that idea that they don't even want someone to know that it's happening. We made a point of emphasising the benefits of sharing data either with oneself in the future or with others and the idea that that ties into how you promote the research that's coming up of your work. Some of the PhD candidates were interested in the fact that we might want their data along with their theses but we also found it helped to be realistic about the obstacles. There's no point pretending that it's easy to share data especially in a situation that I've described before where we had no policy or storage to support our discussion but also that researchers really appreciated as demonstrating that we understood where they were coming from and that their concerns about sharing their data are legitimate and we were able to change some perspectives just because we were prepared to talk about the negatives. So it could in the future be a great outcome for us as data trainers or people encouraging people to share data if we are able to address these issues in a public form and ameliorate them but we can only do it if we actually do say well you know there are some reasons why you might want to share your data or you might want to restrict your data or those kinds of things. So we put up this slide in the presentation so that we could show that we were aware of some of the problems that you know there were time restrictions and the terrible issue of missing incentives as far as data so it's very clear return on publications you get points but nobody rewards you for sharing your data. So we put this slide up merely to show that we understood. We found that tools were really helpful it actually in our situation where we don't have a lot of practical tools to help researchers that having even one or two was really useful. So we have a very active supercomputing function here at Swinvern which is available to the astrophysicists who run it but also everyone else at the university and that's quite long-standing and that's a really useful service but there's not a lot of thinking at the university other than what's happening in the library about how to manage the data. Our data management checklist we went through very briefly in the session and talked about how if you complete this checklist then you should be able to have the rudimentary elements required for a data management plan. Without a policy it's very difficult for us to enforce people making those plans but it does at least allow them to think about the things that they need to think about if they want to look after their data in the future. And our checklist is influenced by Monash and QUT and available from our website. We found that a good example is gold and especially a local example if possible and luckily we had one and it just kind of came up in conversation something that someone said made me think about it. We have this software evolution data set which is prepared by one of our researchers and he makes it available through a website for the project with clear details on how to cite the work and also under a creative commons license so the reuse qualifications are very clear. We've cut a lot of this data set and it's now available through research data Australia but it was nice to be able to show that someone at Swinburne had been able to do this and it wasn't so very hard and that there was also something to be gained from it. The Dean of ICT who was present at the time talked about how in particular in the computer science sphere you can tie the open data movement into other open movements like music and computer science where it was shown over many years that exposure was sometimes of more value than loyalties and that was a particularly good concluding point for those who'd been so concerned about the monetary value of their data. We might have been there to talk about the value of good data management and planning but we still had to be willing with the kind of session that we set up to change the tack of the discussion if it was going in a particular direction. So we had to adapt our presentation on the fly to take account of the audience being mostly early career researchers so they weren't awarded research grants with the ARC and therefore it was difficult for us to say that they were as subject to the responsibility of good data management as say their professors. We would have had to think a bit differently if the senior professors had been present. So the draft data pop sorry hard one draft data management policy was prepared incorporating feedback from this session. It hasn't actually been ratified yet but we made a start. Terence's since returned to the US and Sonya's been teaching but she's returning to research next year. Swindorn has a metadata stores project at the moment and once we have working software installed it would be good to use this as a catalyst for having a follow-up session with some more practical examples more like ANU is doing. At the moment the library research data page is the only one in the university that provides advice on where to go for data analysis support software training in SPSS and R and other statistical software packages and also a list of data repositories in particular subject disciplines that might be useful and the checklist is available there as well to assist with planning and my advice to you if you're starting out in data management training is talk to someone else who's tried it before you. They're my contact details. Are there any questions?