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Developing Liaison Librarians Data-Intensive Research Engagement

At NCSU, librarians have developed a curriculum which is being offered to the library community as the Data and Visualization Institute for Librarians, enabling participants to develop knowledge, skills, and confidence to communicate effectively with researchers.This presentation will discuss the skills liaison librarians must now learn to support faculty and students in these new areas.

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Developing Liaison Librarians Data-Intensive Research Engagement

  1. 1. Developing Liaison Librarians for Data-Intensive Research Engagement Hilary M. Davis & Honora N. Eskridge NC State University
  2. 2. Top 3 take-aways ● Train for exposure ● Develop for depth ● Put it into practice Generalist with Broad Knowledge Domain/SubjectExpertise FunctionalExpertise
  3. 3. Forces that are shaping change Research is changing Subject liaison roles are changing
  4. 4. Our story 2014
  5. 5. Training options Needs for “short-course” experience: ● Hands-on ● Lay a foundation ● Exposure to methods and tools ● Integrate with work/projects ● Community of practice
  6. 6. Poll How many of you have done or are going to conduct on-site group training in data science, data management, and/or data viz?
  7. 7. In-house Data science short course Oct 2015
  8. 8. Data & Viz Institute for Librarians May 2016
  9. 9. Curriculum Team Objectives: ○ Effectively use language of data science to communicate with researchers. ○ Demonstrate basic methods of exploring and analyzing data. ○ Apply visualization techniques to improve data communication. ○ Learn tools and techniques for version control. ○ Understand data sharing requirements of publishers and funding agencies. ○ Understand impact of open research practices.
  10. 10. Sessions Whole- and Half-day Workshops 1-hour Short sessions ● Data exploration & statistical analysis ● Data visualization ● Data description, sharing, & re-use ● Data cleaning and preparation ● Gathering & analyzing textual data ● Gathering and analyzing multimedia data ● Bibliometric Network analysis using Sci2 and Gephi ● Open Science: Version Control with Git and Github ● Open Science: Overview ● Data use agreements and open data
  11. 11. Logistics Team ● Hotel ● Food - Breakfast/lunch/reception ● Transportation ● Space ● Computers and IT support ● Website ● Training materials ● Cost
  12. 12. Leadership Team
  13. 13. Feedback “What a unique and wonderful learning opportunity for librarians. I really think it hit the mark for so many of that are starting out…” Good ● Data viz ● Statistical data exploration ● TAs ● Hospitality Bad ● Need more hands-on ● Need more networking ● Procrastinating instructors ● Staff time Ugly ● Instructor with 240 slides ● Jury duty ● Intensive computing prep ● Power for laptops
  14. 14. What’s next Data Science & Viz Institute for Librarians: April 24-28, 2017 IMLS-funded project: Data Science in Libraries
  15. 15. Going Forward
  16. 16. Thanks!