Immersive informatics - research data management at Pitt iSchool and Carnegie Mellon University Libraries
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The document discusses a research seminar on data management and libraries, highlighting the essential roles of various data professionals, including data librarians and data scientists. It emphasizes the importance of immersive training for students and the need for improved collaboration between researchers and librarians in managing research data. The document also details educational initiatives at the University of Pittsburgh focused on equipping students with practical data management skills and advocating for effective data stewardship.
![A centre of expertise in digital information management
Why Data Management Services?
"The Board believes that timely attention to digital
research data sharing and management is fundamental
to supporting U.S. science and engineering in the twenty-
first century.
...strong and sustainable data sharing and management
policies [are] a critical national need."
Digital Research Data Sharing and Management
December 2011
Task Force on Data Policies
Committee on Strategy and Budget
National Science Board](https://image.slidesharecdn.com/kw-lrsillinois2014-25sep-150313095347-conversion-gate01/85/Immersive-informatics-research-data-management-at-Pitt-iSchool-and-Carnegie-Mellon-University-Libraries-31-320.jpg)
Immersive informatics - research data management at Pitt iSchool and Carnegie Mellon University Libraries
- 1. ImmersiveInformatics - RDM at Pitt iSchool Library Research Seminar VI, Illinois, October 2014 Professor Liz Lyon, School of Information Sciences, University of Pittsburgh
- 2. Agenda 1. Data, RDM and Libraries 2. The “immersive” model 3. Value and Benefits
- 4. Implications of “Big Data” and data science for organisations in all sectors Predicts a shortage of 190,000 data scientists by 2019 http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innov ation/Big_data_The_next_frontier_for_innovation
- 5. Flavours of data scientist (Lyon 2012) • data engineer - focus on software development, coding, programming, tools • data analyst – focus on business/scientific analytics and statistics e.g. R, SAS, Excel to support researchers and modellers, business • data librarian – focus on advocacy, research data management / informatics in a university / institute • data steward – focus on long term digital preservation, repositories, archives, data centres • data journalist – focus on telling stories and news
- 6. New roles New skills …data librarian, research data services manager, data scientist, technical data co-ordinator, data curator, data analyst, data steward, chief data officer....
- 8. “Very few librarians are likely to have specialist scientific or medical knowledge - if you train as a research scientist or a medic, you probably won’t become a librarian.” RLUK/Mary Auckland: Reskilling for Research 2012
- 10. How best to make the domain connection? ImmersiveInformatics pilot development 2013 http://immersiveinformatics.org/ Co-developed UKOLN Informatics + University of Melbourne Focus on work-based RDM training IDCC14 paper
- 11. Librarians & researchers mix 10 modules Immersive data sessions in labs Co-curate dataset Keep “data diary” Positive evaluation
- 12. Next step: Bring the immersiveinformatics model to iSchool data education programs • Visiting Professor @Pitt from January 2014 • Spring Semester – new Research Data Management course first run as a Doctoral Seminar Program Special Topic
- 13. Methodology • 12 student participants for immersive session scheduled for Week 8 Weds 26 February • Doctoral students from Pitt (2), practicing librarians from University of Pittsburgh (2) and from Carnegie Mellon University (8) • Lab placements set up by email / phone via contacts and recommendations • Immersive session for up to 3 hours in the lab • Students work in pairs with a researcher • Briefing note sent to Pitt faculty/researchers • Students briefed during the RDM course
- 14. RDM Course @ Pitt iSchool 1. Introductions & Overview 2. Data Landscape 3. Universities & Data 4. Data Requirements & Capability 5. RDM Roadmaps, Strategy, Services & Structures 6. Data Management Plans 7. No Class – Fall Break 8. Immersive session with Researchers 9. Disciplinary Data 1 10. Legal & Ethical Issues 11. Disciplinary Data 2 12. Data Centers 13. Data Advocacy, Skills, Training 14. Data Sustainability & Costs 15. Presentations
- 15. Immersive Unit Objectives Students will be able to: • Observe research data practice “at the coalface” in a selected discipline or sub-discipline • Learn about disciplinary data creation, capture, collection, manipulation, analysis etc. • Understand data methodologies, tools, protocols, instrumentation, workflows etc. • Build first-hand experience of the day-to-day data challenges and constraints for researchers • Begin to provide RDM advocacy, advice and guidance to researchers
- 17. Fall Semester 2014 RDM & RDI • Research Data Management run as a MLIS Masters course • New Research Data Infrastructures (RDI) Doctoral Seminar Program Special Topic • Student participant numbers (Total=9) and includes Librarians from Pitt and CMU • Immersive session RDM in Week 8 and RDI in Week 7 - up to 3 hours length in the lab
- 18. Research Data Infrastructures 1. No class Labor Day 2. Introductions, Syllabus Overview & Data Storage Part 1 3. Data Storage Part 2 4. Data Publication & Citation Part 1 5. Data Publication & Citation Part 2 6. Data Discovery 7. Immersive session with Researchers 8. Disciplinary Data 3 9. Data Standards 10.Data Repositories 11.Data Preservation (Long-term) 12.Citizen Science, Citizen Data 13. Data Science 14. Data, Society, Futures 15.Presentations & Summary Evaluation
- 19. RDM & RDI Fall Semester 2014 immersives Biomedical engineering
- 20. Evaluation feedback • Collected from faculty and researchers via 1 hour focus group in department – Semi-structured interview approach • Collected from iSchool students via questionnaire completed in class – What worked well? – What didn’t work at all / less well? – What did you learn? – How were Timings? Environment? – How can the placements be improved?
- 21. Student feedback “It was great to see a real-life example of how a lab generates and uses data.” “We learned not only about the specifics of their research but about the lifecycle of data.” “This was a valuable experience. It was very practical and illuminated some of the struggles that one may encounter in discussing data as its own area of research.”
- 22. Faculty / Researcher feedback “We talked about the project, I took them to the lab, showed them cells, raw data, calculations, final data, data which is stored and shared with the PI, details kept in notebook, reagents, primers, antibodies, PubMed, gene databases” “Explaining what one does to a new person is instructive, since it shows you what you do not understand and cannot explain. Discussion with the (LIS) student exposed some weaknesses in my own thinking”
- 23. Process / methodology feedback • Fall Semester RDM & RDI courses will have: – more background information to Faculty e.g. Propose agenda for session – more guidance to students e.g. suggested questions to faculty, topics to explore – Class debrief sessions “More communication needed beforehand – context, agenda” (Faculty) “a debriefing to compare notes either in the pairing or as a larger group” (Student)
- 24. Value & benefits for libraries CMU experience – Keith slides
- 25. A centre of expertise in digital information management
- 26. A centre of expertise in digital information management • It is likely that the way that researchers publish, assess impact, communicate, and collaborate will change more within the next 20 years than it did in the past 200 years. http://book.openingscience.org/
- 27. A centre of expertise in digital information management Useful knowledge Useful knowledge Sharable knowledge Sharable knowledge
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- 29. A centre of expertise in digital information management Research collaboration is associated with high academic and wider impact International collaboration is associated with high academic impact Data can be shared easily across borders
- 30. A centre of expertise in digital information management More data will be created in the next five years than has been collected in the whole of human history. Properly managed, this data will form a major resource for Australian researchers.
- 31. A centre of expertise in digital information management Why Data Management Services? "The Board believes that timely attention to digital research data sharing and management is fundamental to supporting U.S. science and engineering in the twenty- first century. ...strong and sustainable data sharing and management policies [are] a critical national need." Digital Research Data Sharing and Management December 2011 Task Force on Data Policies Committee on Strategy and Budget National Science Board
- 32. A centre of expertise in digital information management • The rapid development in computing technology and the Internet have opened up new applications for the basic sources of research — the base material of research data — which has given a major impetus to scientific work in recent years. • Access to research data increases the returns from public investment in this area; reinforces open scientific inquiry; encourages diversity of studies and opinion; promotes new areas of work and enables the exploration of topics not envisioned by the initial investigators. • The value of data lies in their use. Full and open access to scientific data should be adopted as the international norm for the exchange of scientific data derived from publicly funded research.
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- 38. A centre of expertise in digital information management 3 8 Institutions are to retain research data, provide secure data storage, identify ownership, and ensure security and confidentiality of research data Researchers are to retain research data and primary materials, manage storage of research data and primary materials, maintain confidentiality of research data and primary materials.
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- 41. A centre of expertise in digital information management “The Holdren Memo” To achieve the Administration’s commitment to increase access to federally funded published research and digital scientific data, Federal agencies investing in research and development must have clear and coordinated policies for increasing such access. Memo on Increasing Access to the Results of Federally Funded Scientific Research White House Office of Science and Technology Policy February 22, 2013
- 42. A centre of expertise in digital information management Current priorities in academic libraries 1. Continue and complete migration from print to electronic and realign service operations 2. Retire legacy collections 3. Continue to repurpose library as primary learning space 4. Reposition library expertise and resources to be more closely embedded in research and teaching enterprise outside library 5. Extend focus of collection development from external purchase to local curation Lewis (2007); Webster (2010, 2012)
- 43. A centre of expertise in digital information management • The part that academic librarians should play remains unclear • Raise awareness of eResearch amongst library staff • Provide advice on data management to eResearchers • Data curation is vast, complex and requires subject input
- 44. A centre of expertise in digital information management • “The bad news is that I’m not sure they understand what goes on in the library other than taking out books.” Benton Foundation, 1996 • “User perceptions negatively affect the ability of librarians to meet information needs simply because a profession cannot serve those who do not understand its purpose and expertise.” Durrance, 1988
- 45. A centre of expertise in digital information management The worst thing about the stereotype is that it impacts on the psyche of librarians who really begin to believe that they don't deserve the kingpin role US Congress, 2001
- 46. A centre of expertise in digital information management CORE SCHEMA, Body of Professional Knowledge, CILIP, 2004
- 47. A centre of expertise in digital information management Collections grid high low lowhigh stewardship uniquenessBooks Journals Newspapers Gov. docs CD, DVD Maps Scores Special collections Rare books Local/Historical newspapers Local history materials Archives & Manuscripts, Theses & dissertations Research, learning and administrative materials, •ePrints/tech reports •Learning objects •Courseware •E-portfolios •Research data •Institutional records •Reports, newsletters, etc Freely-accessible web resources Open source software Newsgroup archives http://www.slideshare.net/lisld/collections-grid
- 48. A centre of expertise in digital information management Librarians’ competencies profile for RDM Key roles • Providing access to data –Identification of data sets; discovery and analytic tools; advice on informatics • Advocacy and support for managing data –Policy development; articulating benefits; promoting data sharing and reuse; education and training; data audits • Managing data collections –Preparing for data deposit; appraisal; selection; ingestion; curation; preservation; storage and backup 48
- 49. A centre of expertise in digital information management Core competencies • Providing access to data –Data centres and repositories; organization and structure of data; licensing and IP; manipulation and analysis • Advocacy and support for managing data –Research funder mandates; DMP; research workflows; disciplinary norms; journal requirements; data audit and assessment tools • Managing data collections –Metadata; discovery tools and indexing; database design; data linking; forensic procedures in data curation 49 Librarians’ competencies profile for RDM
- 50. A centre of expertise in digital information management Data Management at CMU Timeline July 2013 September 2013 November Dean appointed Data Management Services Group DM Librarian appointed
- 51. A centre of expertise in digital information management December 2013 January 2014 February 2014 Initial presentation to Faculty Senate Faculty Senate resolution CLIR Data Curation Fellows
- 52. A centre of expertise in digital information management March 2014 April 2014 May 2014 Draft detailed strategy Initial consultation First ‘graduates’ from LIS2975
- 53. A centre of expertise in digital information management What might our service offer? • Teaching or doing? • Compliance or support? • Storage or registering? • Policy advice vs policy development • Institution-wide or in response to requests? • Advising on data re-use (sources, analysis etc)
- 54. A centre of expertise in digital information management Core SteeringSupport Collaboration
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- 57. A centre of expertise in digital information management uqkeithw Keith Webster k.webster@library.uq.edu.au kgw@cmu.edu cmkeithw Keith Webster
- 58. Thank you
Editor's Notes
- #32: These recent calls for data sharing infrastructures have lead to more and more specific suggestions and directives
- #42: Ultimately (in some ways) leading to the now famous “Holdren Memo” Coming out of the White House OSTP - this memo, in six glorious pages, has to potential to drastically change the landscape around data sharing at places like CMU
- #55: And we wound up with these groupings Core steering group with Research, Libraries, and Computing Groups playing supporting roles (OSP, elements of the libraries) And groups interested in Collaborating (or just watching)