Liz Stokes, UTS: Research Data Management training for Librarians
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Liz Stokes, UTS: Research Data Management training. The case for discussing both rdm and data science training needs, and how the library community frames rdm training for librarians. See the video of this presentation: Snippet (YouTube 55 seconds): https://youtu.be/_2UmHbI_yAw Full recording (YouTube 8:40min): https://youtu.be/ZB6S5AtLlYk Full transcript; https://www.slideshare.net/AustralianNationalDataService/transcript-meeting-the-most-unmet-need-rdm-training-for-researchers-hdr-students-and-data-trainers
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Liz Stokes, UTS: Research Data Management training for Librarians
- 1. Research data management What are we training Librarians for? Liz Stokes @ragamouf Data Librarian UTS Library
- 2. Research data management = the future of libraries
- 4. How you say… RDM?
- 6. • ResBaz for communities • Embed RDM in research support • Integrate librarians in eResearch projects 1 0 1 1
Hinweis der Redaktion
- This question: what are we training Librarians for, has been weighing heavily on my mind. So today I want to talk about how the library community frames RDM, for our own development as well as meeting our client communities needs, and what’s been happening at UTS.
- I’m going to use events at UTS over the last year as a case study to answer this question. When I started at UTS, my plan was simple: Teach RDM to my colleagues and turn them all into data librarians Provoke the university into action on RDM by any means necessary Figure out what works Do more of that. But, it wasn’t that simple.
- It might be the future, but it’s hard to promote the future when it looks like just another web form. AT UTS RDM is largely driven by an asset management imperative (which is important!) DMP for all projects including HDRs Stash records mandatory too for any researchers publishing data (even as supplementary to journal article). Library responsible for RDM training eResearch group in ITD develops the infrastructure.
- However, I’m increasingly uncomfortable that RDM and DMP are terms by and for librarians, that RDM is an artificial construct as much as a DMP, which is more often than not an administrative requirement or matter of compliance, rather than an actual thing that supports the doing of research. I’ve realised that my anxiety around RDM has come from the responsibility of persuading my colleagues to make space for a new area of expertise which is still as relatively abstract as the myriad training resources and online courses that are available to learn it, while still remaining fully committed to BAU. Moreover, I learnt how to be a data librarian from doing it, not doing a course. By working on projects, partnering with researchers, the skillset required had more in common with a data scientist than a ‘traditional” Librarians. As a data librarian, a growth mindset and problem solving skills are potentially more valuable than the myriad pieces of the puzzle that make up the matrices of RDM lifecycles and modules.
- So at UTS, we’re developing new offshoots to complement our RDM training. Internally, the IS department is piloting a tinker time project using learning analytics expertise from UTS data scientists to develop our growth mindset and data literacies. EG I’m in a little affinity group of amateur game developers, so my project will follow Bogan the Librarian who must curate research data for a death metal cultural studies researcher. Developing introductory data management (mainly cleaning) and data visualisation skills for UG faculty classes Promoting open datasets for teaching as part of open educational resources for academic teaching staff. These are not strictly in the RDM world, but they are gateway drugs toward it. Shall we call it seeding the commons?
- Speaking of other RDM by stealth initiatives,. The recent Sydney ResBAz that we hosted at UTS in July is a good example of RDM stealth. Research students and staff want data science training and support in data management tools, applications and software. They want to know what will help them, how to do research faster, smarter, more competitively. From our ResBaz pilot in July, we found out that they want to build community, and learn about research tools across disciplinary and institutional boundaries. This is where we embed RDM by offering training in open source tools and software, for example version control which is integrated in github. At ResBaz we presented a generic RDM workshop alongside the coding and software skills. It was the 2nd highest most popular item in responses to the initial EOI for ResBaz workshop content. I don’t know about you but we don’t get 40+ people registering to our regular RDM workshops. This year, at an executive level, UTS has also established a Joint Steering Committee in eResearch and RDM training, which will allow us to embed RDM training within a broader spectrum of specialised research support and data science services. Finally, we’re integrating librarians into eResearch infrastructure projects in two ways: By giving them roles as the go to trainers for specific research tool training, (such as lab notebooks and in the future; REDCap). Also, by giving librarians roles in user acceptance testing of our in house RDM tool (Stash) we can engage them as experts developing data librarian skills.
- So to answer the question I started with, this is what we’re training Librarians for: 3 roles as active participants in providing enhanced research support services. As instructors delivering ‘real data management skills’, from UG through to researcher communities As Advisors delivering RDM by stealth As Engaged Librarians collaborating in eResearch infrastructure development, who can knowledgably refer clients to more specialised data services in a triage type model – eg stats instruction or high performance computing.