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Emerging Role of UC Libraries in
Research Data Management
Education
Kristen Burgess, MSLS
Clinical & Research Informationist
RDAP 2014, March 26-28, San Diego, CA
Emerging Roles: Space
Emerging Roles:
Instruction & Workshops
Emerging Roles:
Instruction & Workshops
NECDMC Modules for UCL DMP
What content or case-related information did you like
best in the module? Why?
Select Questions
•Module 1, Q1: How well did this module prepare you to explain what research data is?
•Module 2, Q1: How well did this module prepare you to explain what a research data set is and the range
of data types?
•Module 4, Q1: How well did this module prepare you to understand why data storage, backup, and
security of research data are important?
•Module 5, Q1: How well did this module prepare you to explain ownership considerations related to data
sharing?
Not at all well Neutral Very well
Answer Scale
%ageofrespondents
Lessons Learned: Teaching DMP to Librarians
• (semi) flipped classroom
• Lots of hands on (but takes time!)
– Good case studies are key
– Favorite exercises: Institutional resources scan,
file naming and folder structure exercise, data
storage case discussion, data de-identification
activity
• Focus on importance of DMP for research but
also for our own day-to-day work and library
research --- “practice what we preach”
Best Practices
• Collaboration & relationship
building
• External & Internal
• Internal training
• Marketing
• Administrative support
Next Steps
• New hires
• Space redesign
• Continuing data consultations &
partnerships
• New workshops
Thanks!
Kristen Burgess, MSLS
Clinical and Research Informationist
Health Sciences Library, University of Cincinnati Libraries
kristen.burgess@uc.edu

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RDAP14: Emerging role of UC Libraries in research data management education

  • 1. Emerging Role of UC Libraries in Research Data Management Education Kristen Burgess, MSLS Clinical & Research Informationist RDAP 2014, March 26-28, San Diego, CA
  • 5.
  • 7. What content or case-related information did you like best in the module? Why?
  • 8. Select Questions •Module 1, Q1: How well did this module prepare you to explain what research data is? •Module 2, Q1: How well did this module prepare you to explain what a research data set is and the range of data types? •Module 4, Q1: How well did this module prepare you to understand why data storage, backup, and security of research data are important? •Module 5, Q1: How well did this module prepare you to explain ownership considerations related to data sharing? Not at all well Neutral Very well Answer Scale %ageofrespondents
  • 9. Lessons Learned: Teaching DMP to Librarians • (semi) flipped classroom • Lots of hands on (but takes time!) – Good case studies are key – Favorite exercises: Institutional resources scan, file naming and folder structure exercise, data storage case discussion, data de-identification activity • Focus on importance of DMP for research but also for our own day-to-day work and library research --- “practice what we preach”
  • 10. Best Practices • Collaboration & relationship building • External & Internal • Internal training • Marketing • Administrative support
  • 11. Next Steps • New hires • Space redesign • Continuing data consultations & partnerships • New workshops
  • 12. Thanks! Kristen Burgess, MSLS Clinical and Research Informationist Health Sciences Library, University of Cincinnati Libraries kristen.burgess@uc.edu

Hinweis der Redaktion

  1. Kristen Burgess, University of Cincinnati Health Sciences Library The University of Cincinnati Libraries (UCL) are pursuing new roles and initiatives to better support research data services, including the creation of a robust research data management and curation training program. Much of this change was initially prompted by the arrival of our new Dean who is pushing the libraries to dramatically alter our role and relationship with campus partners to meet the teaching, research, and healthcare missions of the university. As we’ve moved forward with these exciting initiatives, it’s clear that the broader campus is open to the libraries getting involved in data education and support. In this quick presentation, I’ll discuss a few of the areas where we’re focusing.
  2. Physical Space developed for data consultation services and research-intensive computing. Research Commons - Science & Engineering Libraries - Large scale visualization theatre, collaboration spaces, high end computing, Repurposing of existing space, Collaborative project with UCIT Informatics Lab – Health Sciences Library - Collaboration & consultation spaces, High end computing Digital Space – UCL is developing a next-generation, open access digital repository based on the Hydra framework with an eye toward support of data publishing and curation. Goal is to help meet data intensive needs of researchers from across the institution Collaborative project with UCIT, Office of Research, and colleges like our College of Design Art Architecture and Planning Our Dean’s involvement with this project spurred the creation of a UCL software R&D unit Flexible and module system based on the open source Hydra framework (Fedora)
  3. Instruction & Workshops - In fall 2013, the Health Sciences Library developed a series of research workshops to explore faculty interest in integrated research topics, including a class on data management planning and another on data sets and statistics. Really well received and have continued offering intro DMP workshops across campus.
  4. The HSL is also creating a course for the College of Medicine’s new Medical Sciences major called Informatics and Data for the 21st Century Medical Professional. This curriculum will have an entire data management module focused on data management skills in the medical sciences.
  5. To enhance our initial work on data management support, the health sciences library has also joined the New England Collaborative Data Management Curriculum pilot with plans to implement several of the modules in a variety of settings (standalone workshops, lab groups, etc.).
  6. Initial pilot workshops for our library liaisons just finished last week. We piloted 4 modules – 2 classes per week for 2 weeks. Modules: (1) Overview of RDM, (2) Types, Formats, and Stages of Data, (3) Data Storage, Backup, and Security, (4) Legal and Ethical Considerations for Research Data. Notice a neat aspect of the pilot is each module includes an initial reading, PPT, case activities, and not shown here but a whole list of data specific case studies that can be used in the workshops.
  7. Class went over really well. We had 15 consistent library attendees for all 4 sessions that all gave fantastic feedback for us to use as we tweak the modules for future workshops. Favorite activities included the hands on nature of the exercises as well as the use of cases.
  8. We asked people a number of different questions about how well the modules prepared them to explain different aspects of research data management and as you can see an overall majority answered 4s (well) and 5s (very well) versus 3 (neutral and below) These are just 4 select questions from much longer surveys for each module to highlight the general positive reaction. We plan to publish more about this in the Journal of eScience Librarianship later this year. The great thing was that while we used the STEM-focused cases provided by the pilot project, the cases and overall pilot worked really well across all our librarian backgrounds (only 3 attendees are STEM focused librarians – the rest are humanities). One piece of advice for the collaborative is to create some more social science/humanities focused data cases. While majority of participants told me verbally this is all really new to them, a pre-test would be a great addition to the curriculum.
  9. New Hires & Training - The library is in the early stages of extensive workforce transformation, including the development of several new strategic positions supporting research data and training for library professionals. Hiring Research Informationist and Science Informationist. More coming in the future! Check out our employment page for exciting opportunities! Plan to implement several modules of New England Collaborative Data Management Curriculum in a variety of settings in spring 2014. Additional instruction sessions will be held for specific lab groups on data management specific to their setting, and broader instruction to health sciences undergraduate and graduate students. New topics include metadata, sharing & reuse, archiving & preservation in addition to the 4 modules already piloted.