 All right, so, as Susanna just said, my name's Jane Frazier and I am a data librarian here at ANS. I'm currently working on projects surrounding metadata for research data Australia training for librarians, some restructure and work on our ANS content providers guide, working with partner institutions on data and RDA metadata consultancy, and on some projects surrounding controlled vocabularies. So, because data librarianship is an emerging field, it can be kind of difficult to define exactly what it is, and I've just added a couple of different definitions here, but if I had to describe my own personal definition of a data librarian, or at least what I do as a data librarian, I suppose it would be enabling and supporting researchers by facilitating the description, preservation, publication, sharing, discovery, and reuse of their research data. But you might be thinking, aren't there a lot of people with other job titles that perform a lot of those same duties as well? And yes, you would be correct. There are. Although my official job title is data librarian, there are tons of other people with completely different job titles who do the exact same types of work as me. My official job description includes things like participation in internal ANS projects, collaboration with ANS partners in support of data management projects, providing knowledge and support relating to research data management. Although I will admit that these are pretty broad statements and don't really capture what I am actually doing day-to-day in my job. So before I go into the work that I do day-to-day, I will mention that the path that I took to become a data librarian is also not a very traditional trajectory into the field. Around 2010, I changed careers after spending about eight years in music, academia, and as a professional singer. And I really do think that I learned some of my most valuable professional lessons during that time. So I was doing constant collaboration with colleagues. I had to learn self-motivation and persistence to always keep learning and improving when external encouragement was really rare. I learned how to be able to network and sort of be able to pitch myself. Being able to give and receive constructive criticism was a really, really great tool that I gained. And I learned the fundamentals of humanities research and the principles behind academic writing. After I decided that I didn't want to be a professional musician for the rest of my life, I decided to move into the field of music librarianship. I began library school as a graduate student worker in the UNC Music Library where I learned how to catalog music materials and became familiar with the processes surrounding description of bibliographic materials. I also learned about the basic fundamental academic library processes. That job that I had as a graduate student was really my only experience that I've had personally working in a quote-unquote traditional library environment. However, I wasn't actually working on incoming music materials like a more traditional music cataloger would. I was working on cataloging a special collection of 20th century American sheet music. While I was in library school, I also became interested in technology in libraries, metadata research and information architecture. So I decided to shift my focus to information science. So I began working as a data curator at Dryad, which is a digital repository for data underlying publications primarily in the biosciences. Compared to the cataloging I did in the music library, Dryad uses the d-space repository system and has an underlying schema based primarily on Dublin Core with some other elements, whose standards I personally found much more accessible and intuitive than Mark, which was what I was using to catalog in the music library. I had actual contact and negotiation with authors and journals rather than only having other librarians as sources of support, and that made me feel a lot more connected to the content I was managing and to the people who actually had created that content, which was really fantastic. The multiple workflows I used while a curator at Dryad were a lot less straightforward than those I had been using in music cataloging since sort of the concept of acquisition of data is different than that in a traditional library setting. Because I also worked with developers, I was able to give feedback on my own use of the system and was able to provide input in its development, which was really another great thing that helped me learn about the data curation lifecycle. There was a lot more variety from item to item that I was working on because of the variety of types and formats of data being submitted to Dryad. While I was working at Dryad, I also, at the same time, worked as a research assistant at the UNC Metadata Research Center, and this was a really, really valuable job for me to have at the same time that I was at Dryad because I was able to gain a much higher level understanding of my Dryad work by doing research on those practices surrounding curation and data description that I was doing day to day at Dryad. And I also became familiar with collaborative research processes and experience with grants that I hadn't had previously when I was doing music research. After library school, I was offered a job as a product manager at a collectibles company called Stanley Gibbons. At the time, I had no idea what a product manager was exactly, talking again about the completely different job titles for very similar types of jobs, but the job description that went along with this product manager job was exactly what I was wanting to do. So my work at Stanley Gibbons involved working with engineers and stamp catalogers or stamp describers to develop a new cataloging system for postage stamps and other collectibles. So this is a non-traditional cataloging system. I was in a really fast-paced and highly collaborative environment with developers and management folks and users of the system. I worked in requirements gathering and learned how to sort of find out what users really want, even if they don't know how to articulate it, which is a very, very valuable skill, I think, in this field. I gained experience with agile software development and really did learn how to fail fast and pivot after failing and figure out how to solve the problems. I had to learn how to speak with software developers and marketing people rather than librarians and scientists. So it was incredibly valuable for me to be able to communicate about what I do with less sort of library-centric language, and it was very challenging at first, but I learned a lot about communication in general. Although I learned a ton at this job and I got to work on some really cool projects after working at Stanley Gibbons for about a year and a half, I knew that I wanted to return to the research and academic sector. So I knew that I wanted to be in a position where I could blend my desires to work with librarians and researchers, to work with software development and to provide access to information to help people rather than specifically to make a profit, which was definitely one of the goals at Stanley Gibbons. So I accepted my position as a data librarian at ANZ. I mentioned some of the projects I'm working on a little bit earlier, but my work at ANZ is primarily project-based, which means that I get to deal with lots of different types of problems on a day-to-day basis, and I get to kind of touch on those different projects every day, which is very interesting to me. My day-to-day role as a data librarian includes a lot of different types of skills, like requirements gathering, business analysis, crosswalking, design, writing, training and support, and internal and external communication within ANZ and outside of ANZ. And every day I'm able to use skills that I've learned at all of the stages of my professional development, and I also get to use these skills throughout different projects I'm working on. So I feel like every stage of my professional development and every job that I've worked in, I'm able to use the experience that I got there here as a data librarian. I've also included here a list of tools I'm using at the moment. I'll mention that this list is constantly changing depending on what projects I'm working on, but yes, Google Drive is always my core tool for document storage, organization and sharing, word processing, spreadsheets, diagramming and presentations. This presentation right here is housed in Google Drive. Now I'll talk a little bit about what I see as some of my main challenges in my position, and I really do think that many of these might be similar to challenges faced by all types of librarians. When Natasha asked me to speak of this webinar, she asked me to touch on the challenges of flying solo outside of a traditional library environment, but because I have really little experience working in a traditional library setting, it's kind of difficult for me to compare the two. However, I can say that I definitely feel that I have a really great support system of librarians, developers and other specialist experts made up of colleagues here at ANZ, those that I know from previous work and other people that I've met since I moved here to Australia about eight months ago. I do a lot of different sorts of activities to develop my skills. One thing that I really love about working with data and metadata is that it is, for the most part, or in some instances, discipline agnostic, and this means that I can discuss issues surrounding data with people in any field of research, and I love to use it as a vehicle to learn about new topics. It's sort of a universal problem that anyone can understand in their own context. I also heard a really inspiring quote when I attended the Research Bazaar conference a few weeks ago at Uni Melbourne, and I'm sort of paraphrasing here, but somebody said that if you're here, you are smart enough to solve pretty much any problem that you encounter, so at the time this statement was targeted towards researchers, I do think it really applies to librarians as well, and it really echoes the attitude I try to take toward overcoming the fear of things that I perceive to be just above my skill level, so that helps me kind of overcome that fear if I ever feel it, which is really, really necessary in this field because you're always having to learn new skills and learn about new technologies. I also really love collaborating with developers. I know this might be kind of a generalization, but the devs I've worked with are just classic problem solvers, and I've been able to learn a lot about general analysis and problem solving from their really logical viewpoint. If you are looking to move into a data librarian role, whether it is given that title or not, because often it's not, here are a few things that I personally have found helpful. Like I've said before, although my official job title is data librarian, there are tons of other people with different job titles who do the exact same types of work as me. There are a lot of data librarian jobs out there that just happen to have different titles, so don't be afraid to look at other job titles. Having experience in academia and in the private sector, I can also definitely say that learning to use neutral language to describe what I do is very valuable, and in an interview setting, being able to sort of describe your own skills and language that will be meaningful to the interviewers is really, really valuable. Since starting work at ANS, I've already encountered dozens of new standards and tools, and I would say that this is fairly typical in this line of work, so definitely be prepared to be flexible in that respect. And if you're interested in upscaling yourself, don't wait until there's a project that comes along in which you have to use the technology. I would just say learn it now. If you're interested in it, just try it out. I've included some of the online sources that I recommend here, and there are links embedded in all of these images as well. So I've also included some other resources I'd recommend if you are looking to get into data librarianship here. I will admit that a few of them are pretty American-ness-centric because that's the environment that I come from. But the UNC School of Information and Library Science CILS job search sites are really, really great, and I think they can be useful for anyone anywhere around the globe. So thank you very much for letting me share with you, and yeah, please let me know if you have any questions. What other titles are there for data librarians? Yeah, sure. That's actually a really excellent question, and it's funny because when I initially put together my slides for this presentation, I had a slide that included a word cloud. You know how librarians love to use word clouds of a bunch of different words that were used in data librarian titles, and I did cut that one out. But there are lots of words like support, information, analysis, and a lot of jobs have really, really creative titles. I know that there was one that came up, I don't know, maybe six months ago that was for a socio-informatician, which is a really great name, I think. So it's really, it can be anything. You just have to look past the title and look at the description. There's a library job random generator somewhere online that brings up some hilarious ones, but some of them are a little bit accurate. Yeah, there's such a variety of words to describe what we do that sometimes you look at jobs and think, oh, I have no idea what that is, and it turns out it's a data librarian. They're research coordinator, research manager, data manager, database administrator. A lot of the time are crossover jobs for us. Kat Herder. What advice do you have for information management students who are starting out in the field of data librarianship? My biggest piece of advice to any student studying information management would be just to think big, to really learn your basics and to look at how they can be transferred to other areas. So you learn about metadata. It can simply be the label on a bug being canned. It could facilitate the exchange of data. It enables search and discovery. It's using information architectures. It gives context to data and other information, and it can predict quality. So what you look at, each simple thing can be used in multiple disciplines, and I think that's just what you need to remember is just because you start learning about one thing, it is the foundation that you can use as a link from to other areas. And I actually have something to say to that as well. Yeah, so I know that personally when I was in library school and I was looking to get into this field, one of the things that I did that I found very valuable was sort of reaching out to any person in my area that I thought was doing data librarianship or something similar to it, and I would go and visit them at their work and spend 20, 30, 40 minutes just talking to them about what they did. And it really not only helped me learn more about the field, but it also gave me contacts. So that was a really great thing that I was able to do. Is it ever an issue being constrained by software or infrastructure in the consulting work that you do? How do you manage this or do you try to go to a higher level and sit above this? I'd actually don't get involved in anything related to technology. Totally technology agnostic. I look at everything from an information perspective, so identifying what the value of that information is to an organisation or a business or an individual, a scientist, a researcher, whatever, looking at the flows of the information and the value chain. And if you do get caught up in jumping to solution mode, which is what the technology is, it's in that navel art to make something happen, but it's the information that's the king here. Step back and look at it from either the strategic perspective, so look at the bigger picture. Look at it from a tactical perspective to see, well, by doing this, what will change in the future? Or if need be, you can get into the operational nitty-gritty, but from my perspective, I never deal with technology. I deal with information only. And if I'm working on an engagement or leading a project that gets to a point where they need a piece of technology, then sure, we can make a recommendation along those lines, but we don't actually do anything, but we don't do a technology implementation with that way. We focus purely on data and information, and it hasn't been a problem so far. Given that all three of you have come to your roles basically bypassing traditional library roles, do you think employers are looking for something different in these specialist roles? This begs the question, what can traditional librarians do to make themselves stand out as potential candidates for these type of roles? Yeah, I think they are looking for something different, but I think that's because they don't know what librarians can do to talk to the first part of the question. And I think some of our game plan can be also to make people more aware of what librarians actually do now, because there is this outmoded idea that we're now covered with lots of books, which I would love to be, but that's not what we do anymore in many cases. So to make yourself stand out more as a potential candidate, I think you can make yourself aware of the technologies and begin speaking out perhaps more when you have the opportunity about what people not using library services could have to do with your library services. For example, in cases of storage, that's a really interesting discussion that's going on at universities at the moment. Researchers need storage. Where should they go to get that storage for their data? In some cases it needs to be within the university. For example, if you're employed by the university, sometimes outside. And that's something that we're really well suited as as librarians to start shepherding the conversation or at least bringing that conversation to other potentially useful partners. So maybe one of the best things that's going to happen to us is these larger questions coming up and us speaking out about what we can do. It's very easy to sit in meetings and go, well, somebody will ask about data storage. Someone will ask about metadata. They don't know to ask. We need to be a little bit more forthcoming sometimes. Be the bolshey person at the meeting. That would be my advice. I think you need to be adaptable, really flexible. Use your imagination. Innovate with what you can do. Apply a different perspective. Put your ideas forward. I think all of those things are great. And like Siobhan, I agree. You need to speak up. Put your thoughts on the table, but make them from an information perspective. Because as I said before, the information is coming. Yeah, I actually agree with both Siobhan and Michelle. I think being able to be flexible and sort of step outside of the box, think outside of the box is really valuable and to have other people perceive that you are able to do that. I know that when I was sort of in talks with Dryad about working there, I had really no experience working in data curation. And I hadn't also worked in any type of science or biosciences, but I was really keen to learn and was really interested in sort of immersing myself in both data curation and science data. And I think that that was something that appealed to them. So basically what I'm hearing is get out and do things and let everybody else know what you can do. Fantastic, Siobhan. Yes!