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ImmersiveInformatics -
RDM at Pitt iSchool
Library Research Seminar VI, Illinois, October 2014
Professor Liz Lyon, School ...
Agenda
1. Data, RDM and Libraries
2. The “immersive” model
3. Value and Benefits
http://www.flickr.com/photos/think
mulejunk/352387473/
http://www.google.co.uk/imgres?q=illumina+bgi&hl=en&client=firefox-...
Implications of
“Big Data” and
data science for
organisations in
all sectors
Predicts a
shortage of
190,000
data scientist...
Flavours of
data scientist
(Lyon 2012)
• data engineer - focus on software
development, coding,
programming, tools
• data ...
New roles
New skills
…data librarian, research data services manager, data
scientist, technical data co-ordinator, data cu...
http://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/whitepapers/Tenopir_Birch_Allard.pdf
“Very few librarians are
likely to have specialist
scientific or medical
knowledge - if you train as
a research scientist ...
https://www.flickr.com/photos/23312112@N04/9108008669/in/photolist-eSQVEe-9dju9H-f3rUKg-h2kzk1-8nbYbH-apTJmZ-a8CapW-ahsWNa...
How best to make the domain connection?
ImmersiveInformatics pilot development 2013
http://immersiveinformatics.org/
Co-de...
Librarians &
researchers mix
10 modules
Immersive data
sessions in labs
Co-curate dataset
Keep “data diary”
Positive evalu...
Next step: Bring the
immersiveinformatics
model to iSchool data
education programs
• Visiting Professor @Pitt from January...
Methodology
• 12 student participants for immersive session
scheduled for Week 8 Weds 26 February
• Doctoral students from...
RDM Course @ Pitt iSchool
1. Introductions & Overview
2. Data Landscape
3. Universities & Data
4. Data Requirements &
Capa...
Immersive Unit Objectives
Students will be able to:
• Observe research data practice “at the coalface” in
a selected disci...
Spring Semester
2014 immersives
Fall Semester 2014 RDM & RDI
• Research Data Management run as a MLIS
Masters course
• New Research Data Infrastructures (...
Research Data Infrastructures
1. No class Labor Day
2. Introductions, Syllabus
Overview & Data
Storage Part 1
3. Data Stor...
RDM & RDI
Fall Semester
2014
immersives
Biomedical
engineering
Evaluation feedback
• Collected from faculty and researchers via
1 hour focus group in department
– Semi-structured interv...
Student feedback
“It was great to see a real-life example of how
a lab generates and uses data.”
“We learned not only abou...
Faculty / Researcher feedback
“We talked about the project, I took them to the lab,
showed them cells, raw data, calculati...
Process / methodology feedback
• Fall Semester RDM & RDI courses will have:
– more background information to Faculty e.g.
...
Value & benefits for libraries
CMU experience – Keith slides
A centre of expertise in digital information management
A centre of expertise in digital information management
• It is likely that the way that researchers publish, assess
impac...
A centre of expertise in digital information management
Useful knowledge Useful knowledge
Sharable
knowledge
Sharable
know...
A centre of expertise in digital information management
A centre of expertise in digital information management
Research
collaboration is
associated with high
academic and wider
...
A centre of expertise in digital information management
More data will be created in the
next five years than has been
col...
A centre of expertise in digital information management
Why Data Management Services?
"The Board believes that timely atte...
A centre of expertise in digital information management
• The rapid development in computing
technology and the Internet h...
A centre of expertise in digital information management
3
3
A centre of expertise in digital information management
A centre of expertise in digital information management
3
5
A centre of expertise in digital information management
A centre of expertise in digital information management
3
7
A centre of expertise in digital information management
3
8
Institutions are to retain
research data, provide
secure data ...
A centre of expertise in digital information management
3
9
A centre of expertise in digital information management
4
0
A centre of expertise in digital information management
“The Holdren Memo”
To achieve the Administration’s commitment to
i...
A centre of expertise in digital information management
Current priorities in academic
libraries
1. Continue and complete ...
A centre of expertise in digital information management
• The part that academic
librarians should play
remains unclear
• ...
A centre of expertise in digital information management
• “The bad news is that I’m not sure they
understand what goes on ...
A centre of expertise in digital information management
The worst thing about
the stereotype is that it
impacts on the psy...
A centre of expertise in digital information management
CORE SCHEMA, Body of Professional Knowledge, CILIP, 2004
A centre of expertise in digital information management
Collections grid
high low
lowhigh
stewardship
uniquenessBooks
Jour...
A centre of expertise in digital information management
Librarians’ competencies profile for RDM
Key roles
• Providing acc...
A centre of expertise in digital information management
Core competencies
• Providing access to data
–Data centres and rep...
A centre of expertise in digital information management
Data Management at
CMU Timeline
July
2013
September
2013
November
...
A centre of expertise in digital information management
December
2013
January
2014
February
2014
Initial
presentation
to F...
A centre of expertise in digital information management
March
2014
April
2014
May
2014
Draft
detailed
strategy
Initial
con...
A centre of expertise in digital information management
What might our service offer?
• Teaching or doing?
• Compliance or...
A centre of expertise in digital information management
Core SteeringSupport Collaboration
A centre of expertise in digital information management
55
A centre of expertise in digital information management
A centre of expertise in digital information management
uqkeithw
Keith
Webster
k.webster@library.uq.edu.au
kgw@cmu.edu
cmk...
Thank you
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Immersive informatics - research data management at Pitt iSchool and Carnegie Mellon University Libraries

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A joint presentation by Liz Lyon and Keith Webster on providing education for librarians engaged in research data management. This was delivered at Library Research Seminar VI, at the University of Illinois Urbana Champaign in September 2014. The presentation looks at a class delivered by Lyon at the University of Pittsburgh's iSchool in 2014, and the related needs for immersive training opportunities amongst experienced practicing librarians, using Carnegie Mellon University's library, led by Webster, as a case study.

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Immersive informatics - research data management at Pitt iSchool and Carnegie Mellon University Libraries

  1. 1. ImmersiveInformatics - RDM at Pitt iSchool Library Research Seminar VI, Illinois, October 2014 Professor Liz Lyon, School of Information Sciences, University of Pittsburgh
  2. 2. Agenda 1. Data, RDM and Libraries 2. The “immersive” model 3. Value and Benefits
  3. 3. http://www.flickr.com/photos/think mulejunk/352387473/ http://www.google.co.uk/imgres?q=illumina+bgi&hl=en&client=firefox- a&hs=Jl2&rls=org.mozilla:en-GB:official&biw=1366&bih http://www.flickr.com/photos/wasp_barcode/4793484478/ http://www.flickr.com/photos/charleswelch/3597432481// http://www.flickr.com/photos/usfsregion5/4546851916// Data... evidence, reproducibility, curation, stewardship
  4. 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. 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. 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....
  7. 7. http://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/whitepapers/Tenopir_Birch_Allard.pdf
  8. 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
  9. 9. https://www.flickr.com/photos/23312112@N04/9108008669/in/photolist-eSQVEe-9dju9H-f3rUKg-h2kzk1-8nbYbH-apTJmZ-a8CapW-ahsWNa- a8CXWA-6SEFzn-7DMRoo-4Zudts-TpNW5-4jh869-2MhStX-8tqtLd-8XQvXo-8s9Uup-6GB7QU-995KZ7-7uG7vL-9mgxCa-6qpip1-77mSoG- 7LGBw4-at7uYC-ghoME2-jfbsjF-8rHmyB-khyact-7gWFgw-968oHa-i8gDyd-jrvv7v-hu8KBH-5X3pmT-8LBseT-dMXgXq-fmNe5N-dNuWKB-dNMuxP- brmocc-b9djCp-yKP5Q-dsQ5xw-9HtSRR-eRVdi8-5BncXP-apYD4x-6gQ4mJ-4N6WQv Data curation : domain disconnect ?
  10. 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. 11. Librarians & researchers mix 10 modules Immersive data sessions in labs Co-curate dataset Keep “data diary” Positive evaluation
  12. 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. 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. 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. 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
  16. 16. Spring Semester 2014 immersives
  17. 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. 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. 19. RDM & RDI Fall Semester 2014 immersives Biomedical engineering
  20. 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. 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. 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. 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. 24. Value & benefits for libraries CMU experience – Keith slides
  25. 25. A centre of expertise in digital information management
  26. 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. 27. A centre of expertise in digital information management Useful knowledge Useful knowledge Sharable knowledge Sharable knowledge
  28. 28. A centre of expertise in digital information management
  29. 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. 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. 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. 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.
  33. 33. A centre of expertise in digital information management 3 3
  34. 34. A centre of expertise in digital information management
  35. 35. A centre of expertise in digital information management 3 5
  36. 36. A centre of expertise in digital information management
  37. 37. A centre of expertise in digital information management 3 7
  38. 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.
  39. 39. A centre of expertise in digital information management 3 9
  40. 40. A centre of expertise in digital information management 4 0
  41. 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. 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. 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. 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. 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. 46. A centre of expertise in digital information management CORE SCHEMA, Body of Professional Knowledge, CILIP, 2004
  47. 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. 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. 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. 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. 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. 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. 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. 54. A centre of expertise in digital information management Core SteeringSupport Collaboration
  55. 55. A centre of expertise in digital information management 55
  56. 56. A centre of expertise in digital information management
  57. 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. 58. Thank you

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