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LIBER Webinar: Supporting Data Literacy


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These slides relate to a LIBER Webinar on 12 December 2017, with speakers Robin Rice and John Southall.

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LIBER Webinar: Supporting Data Literacy

  1. 1. WEBINAR: Research Data Services WEBINAR: Supporting Data Literacy The webinar starts at 1400 CET Join the conversation: #LIBERWebinar
  2. 2. Speakers Robin Rice University of Edinburgh Moderating Birgit Schmidt Goettingen State and University Library Rob Grim Erasmus University Rotterdam John Southall Bodleian Libraries
  3. 3. Supporting Data Literacy: Theory and Practice LIBER Webinar Robin Rice & John Southall (Universities of Edinburgh and Oxford) 12 December 2017
  4. 4. Overview – the theory side of things • Why is data literacy important today? • Data literacy within library instruction • The Data lifecycle and RDM training • Understanding the mechanics of data • What has statistical literacy got to do with it? • What about data science? • What data skills do librarians have/need?
  5. 5. Why is data literacy important today? (JOBS)
  6. 6. You say you want a (data) revolution… The number of people with these skills [Core Data Experts] needed to effectively operate the EOSC is, we estimate, likely exceeding half a million within a decade. (Nov. 2016)
  7. 7. New LIBER Strategy: 7 of 15 themes directly relate to data skills 1. Research Data Management 2. Innovative Metrics 3. Diversifying Digital Skills of Library Staff Members and Researchers 4. Digital Cultural Heritage and Digital Humanities 5. Citizen Science 6. Semantic Interoperability; Open and Linked Data 7. Data Stewardship
  8. 8. Data literacy within library instruction • Finding existing data sources • Promoting data citation • Data as a “first-class research object” -, 2014 • Understanding the role of metadata • Open data licenses • FAIR and reproducibility principles • Legal, ethical caveats on data sharing One of the conclusions from the initial EOSC High Level Expert Group was that, with regards to effecting good research data practices, cultural change among researchers represents 80% of the challenge whereas technological change represents only 20%. - Knowledge Exchange (Nov. 2017) “The evolving landscape of Federated Research Data Infrastructures”, p. 28.
  9. 9. The data lifecycle and RDM training
  10. 10. For further study: Research Data MANTRA • Openly licensed, online self-paced learning in RDM • Designed for postgrads and early career researchers • Interactive material - text, images, quizzes • Video stories from researchers with transcripts • + Data handling exercises Downloadable, re-usable units:
  11. 11. Research Data Mgmt & Sharing MOOC (Coursera) Collaboration with UNC-Chapel Hill CRADLE project • Understanding Research Data • Data Management Planning • Working with Data • Sharing Data • Archiving Data •
  12. 12. Understanding the mechanics of data • Data structures and formats • Rectangular datasets • databases • Images • Audiovisual • Text • Big/streaming data • Open formats and digital preservation • Software code – languages and tools for manipulating data
  13. 13. What has statistical literacy got to do with it? • Statistical literacy and statistical competence • Evaluating data as evidence, and statistical claims • Study design • Numeracy: reading tables and graphs • Sample vs universe • Statistical power • Confounding variables • Understanding probability • Null hypothesis • Measures of statistical significance
  14. 14. What’s wrong with this picture?
  15. 15. What about data science? data-science-venn-diagrams.html
  16. 16. What data skills do librarians have / need? • Many librarians come from a non-scientific, non-quantitative academic background(?) • Critical thinking goes a long way • Skilling up is always an option • Try some coding/working at the command line • Many attributes of librarians are needed for data-driven science, scholarship • Advocacy for FAIR principles, policy input, helping to drive culture change • Curation of content and metadata • Facilitating inter-disciplinary work, digital preservation, appraisal • Match-making (researchers and data / repositories; helping students who are stuck) • Helping join-up the data landscape – many disciplines/infrastructures operating in silos Library service metrics • What data do you need to wrangle / analyse to make your services data-driven?
  17. 17. Overview – putting ideas into practice • Reskilling Librarians at the Bodleian • Engagement with wider RDM support • Embedding RDM training and the role of the Bodleian • Termly briefings at the Bodleian • New roles
  18. 18. Reskilling Librarians at the Bodleian • Programme of simple introduction to RDM sessions; • Geared to the particular landscape of University of Oxford • ‘Bodleian Libraries’ as decentralised network of around 60 libraries • Builds on existing training at Oxford • Across divisions – discipline agnostic • High proportion of part time staff • Run twice termly – to increase availability
  19. 19. Training Delivery and feedback • Integrated with staff development system; • Advertised along other staff training • Make use of existing booking and feedback mechanisms • Included in training record of each participant • Feedback • Improved familiarity with RDM as a subject • Greater awareness of its place in day to day activity • Some less sure – but happy to be informed • Variation due to discipline? e.g Natural Sciences more self contained and less reliant on library advice with data handling/ advocating sharing? • Overall more confident
  20. 20. Engagement with wider RDM support • Building on reskilling • From awareness to involvement • Increasing engagement – dealing with research questions which are RDM questions • Beyond citation and bibliographic management to data citation and management • Promoting the usefulness of DMPs as good practice tool • ORA-Data – our data repository • Advocating its use • Top-level understanding how it works and can be contacted • Build on their existing understanding of resource access and licensing • Research Data Oxford • Promoting use of the RDM infrastructure at Oxford • Integrating RDO with library/subject consultant managed ‘libguides’
  21. 21. 3bPic of lib guide with rdm tab • Voluntary take up • More being rolled out
  22. 22. 3bPic of lib guide with rdm tab • Voluntary take up • More being rolled out
  23. 23. Embedding RDM training and the role of the Bodleian • Next steps - Refining initial training • Look for gaps for further innovation • Use existing intelligence gathering and sharing infrastructure • Subject consultant network at University of Oxford • E.g. staff training for Medical Sciences Division librarians • New ‘bespoke ‘training’ • More focussed covering RDM themes for specific events – goals – deadlines • E.g. presentations as part of workshops for post-graduates applying for ESRC funding • E.g. briefings to departmental administrators on latest Wellcome Trust and Horizon 2020 RDM policy • This is promoting RDM issues through meeting needs specific to an institution • Establishing the Bodleian as first point of contact for RDM
  24. 24. Termly briefings at the Bodleian • Keeping data management in view of the Bodleian • Keep it relevant to needs of librarians and readers • Another way to keep training content up to date • Termly data briefings • Short meetings held every term: Michaelmas, Hilary and Trinity • Include invited speakers from ‘data centric’ researchers at Oxford • Update librarians on RDO and ORA-Data • Hear about their interests and concerns • Another way to keep training content up to date • Create a dialogue on data access, management and preservation
  25. 25. New roles • Data Stewards • Need for data continued data administration after a project • A data sharing co-pilot • Currently defined on a case by case basis – departmental or library based • Solution to particular cases which has created a useful precedent • Identified and recruited through day to day library interaction – consultative committees at Oxford • Or through specialised knowledge of Bodleian subject consultants
  26. 26. Meeting reader demand • Financial Data specialist • Role under development • Filling identified gap – need for library based support in data handling • Recent expertise in finding and handling financial data • Integrate with current training and research interviews • Department of Economics • Said Business School • Accommodating wider use and demand of data across disciplines • e.g ‘financial data’ also being used by; • Sociology – History – Geography – Social Policy – Medicine – Migration Studies – Education etc. • More support needed to allow proper re-use • Funders emphasise role of data creators in preparing for sharing and re-use • Academic Libraries will play a key role in delivering it • Supporting data handling becomes another facet of data literacy
  27. 27. Over to you – questions, comments
  28. 28. WEBINAR: Research Data Services Questions? Type your questions in the chat box. Rob and Birgit will pose questions to the speakers. Unanswered questions will be covered in a blog post. This will be published after the webinar. We’ll email a link to the recording shortly.