This presentation was jointly given by Kevin Read and Alisa Surkis of New York University during the two-part NISO webinar, Digital and Data Literacy, held on September 20, 2017.

1. Facilitating the Development of
Research Data Management Services
at Health Sciences Libraries
Kevin Read, Alisa Surkis

2. Data Services @
NYU Langone Health

3. Data-related Competencies
National Postdoctoral Association
● Establishing data back up protocols
● Sharing of data with collaborators
● Ownership and access to data
Clinical and Translational Science Awards Core Competencies
● Implement quality assurance systems with control procedures for data intake,
management, and monitoring for different study designs.
NIH Rigor and Reproducibility Guidelines
● Require formal instruction in scientific rigor and transparency to enhance
reproducibility for all individuals supported by institutional training grants

4. Training Shortcomings
Lack of data management training
● Barone L, Williams J, Micklos D. Unmet Needs for Analyzing Biological Big
Data: A Survey of 704 NSF Principal Investigators. bioRxiv. 2017.
Need for improved training in data sharing, management and collection practices
● Jahnke L, Asher A, Henry C, Keralis SDC. The Problem of Data. Council on
Library and Information Resources. 2012:1-43.

5. Libraries Providing Data Services

6. NLM New Data Hub at NIH
“NLM is now poised to build on its activities in computational-based research, data
dissemination, and training to assume the NIH leadership role in data science.”
- Advisory Committee to the NIH Director
“The challenges of big data—its size, variability, and accessibility—align with the
strengths of the library. “
- NLM Director, Patti Brennan

7. Widespread data management training
● Basic science institute
● Postdoctoral scholars
● Clinical and translational science trainees
● Individual research groups
Research Data Management @ NYU Langone Health

8. Required 1-credit course for first-year PhD, MD/PhD students
Titled: Fundamental Skills and Tools for Research
Includes:
● Research data management
● Rigor and reproducibility
● Open science/data
● Data visualization
● Git and GitHub
Research Data Management @ NYU Langone Health

9. Data Day to Day Series
● 8-12+ data classes offered 3 times/year
● Mix of library-taught, and classes offered by collaborators

10. Classes offered
Summer 2016 Fall 2016 Spring 2017 Summer 2017
Data Visualization (2) REDCap (2) Intro to R (2) Intro to R (2)
RDM Essentials Data Visualization Data Visualization (2) Data viz w/ggplot2
Intro to REDCap & i2b2 Qualitative Study Designs REDCap (2) Data Viz w/GraphPad Prism (3)
Qualitative Data Analysis QGIS (2) Git & GitHub Git & GitHub
Big Data in Medicine Qualitative Interviews RDM Workshop REDCap (3)
Data Wrangling Intro to R Data Saturation in Qualitative Res. Regression Analysis
Clinical Data Management Research w/ Limited English Pop Research w/Limited English Pop
Hypothesis Testing in R Survey Design
High Performance Computing
Machine Learning
SPSS

11. Data Services Development for
Health Sciences Librarians

12. Continuing education classes for medical librarians
NIH Big Data to Knowledge training grant
National Network of Libraries of Medicine funded pilot
Data Management Training for Medical Librarians

13. Learning Objectives:
● Current roles libraries play in research data management (RDM)
● Research process
● Differences between clinical and bench science researchers and their RDM
needs
● Current climate around data management and sharing
● Best practices in data documentation and description
● Relevance of standards to data management
● Issues in storage, preservation, and sharing of data
Continuing Education for Medical Librarians

14. NIH Big Data to Knowledge Initiative
● Launched in 2014 to facilitate broad use of biomedical big data
● Develop and disseminate analysis methods and software
● Enhance training relevant for large-scale data analysis
● Establish centers of excellence for biomedical big data
Awarded training grant R25 LM012283 2015-2017
● Preparing Medical Librarians to Understand and Teach Research Data
Management

15. Online Librarian Training
Practice of research
Story of data
Fundamentals of RDM
Cohort of biomedical librarians
Varied teaching experience
Slides + script
Evaluation methods
“Edutainment” videos
Observing librarians teach
Follow-up interviews with
librarians
Knowledge gain
Satisfaction
Intent to practice
Dissemination to
Biomedical Library
Community
Piloting
In-person
Curriculum
Knowledge gain & satisfaction
Comfort level/Intent to teach
Qualitative follow-up
Librarians Teaching Researchers
Librarian
Evaluation
Piloting
Web-based
Curriculum
Evaluation
Researcher

16. Online Librarian Training
Practice of research
Story of data
Fundamentals of RDM
Web-based
Curriculum

17. Variable
Name
Field type Description Choices
subject_id Text Unique identifier for each
subject
last_name Text Subject last name
first_name Text Subject first name
birth_date Date Subject birth date
sex Integer Subject sex
RDM Best Practices

18. Variable
Name
Field type Description Choices
subject_id Text Unique identifier for each
subject
last_name Text Subject last name
first_name Text Subject first name
birth_date Date Subject birth date
sex Integer Subject sex
DNA by pedro baños cancer https://thenounproject.com/search/?q=genome&i=182407
lab flasks by Carla Dias https://thenounproject.com/search/?q=lab+animal&i=546042
RDM Best Practices Understanding Research Context

19. Online Modules: Story of Data

20. Online Modules: Data Lifecycle

21. Online Modules: Data Lifecycle

22. Online Modules: Understanding Researchers

23. Online Modules: RDM Climate

24. Online Modules: RDM Best Practices

25. Online Modules: Data Standards

26. Online Modules: Data Standards
NO STANDARD FOR STANDARDS

27. Online Modules: Storage, Preservation, and Sharing

28. Online Modules: Getting Started

29. Sufficient Knowledge to Teach RDM

30. Comfort Level Before and After Modules

31. Other Use of Knowledge Gained

32. Online Modules
http://bit.ly/RDM_Modules

33. Librarians Teaching Researchers
Cohort of biomedical librarians
Interviews with librarians
In-person
Curriculum
Slides & Script
Evaluation materials
“Edutainment” Videos

34. In-Person Pilot
Semi-structured observations of classroom
Evaluation of students for satisfaction, intent to use
Follow-up interview with librarians

35. Previous Training

36. Use of Knowledge Gained

37. Teaching Toolkit for Librarians
http://bit.ly/RDM_TeachingToolkit

38. Data Services Pilot Program

39. National Network of Libraries of Medicine

40. Health Science Libraries
Data Community
NNLM
Region
NYU
Langone
SUNY
Stony
Brook
University
of Buffalo
Temple
University
Drexel
University
University
of
Delaware

41. Health Science Libraries
Data Community
NNLM
Region
NYU
Langone
SUNY
Stony
Brook
University
of Buffalo
Temple
University
Drexel
University
University
of
Delaware

42. Project Goals
Support health sciences libraries in developing a viable research data management
component to their service offerings
Establish a community of librarians and libraries offering data services

43. Project Components
Training
Online Modules: http://bit.ly/RDM_Modules
Service
Teaching Toolkit: http://bit.ly/2s1Nmqg
Data Interviews: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4511052/
Data Series: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370612/

44. Data Interviews

45. Philosophy of why we designed the interviews
Necessary for gaining a better understanding of researchers data management
challenges and opportunities
Identified researchers conducting basic science and clinical research
Used active grant system to identify a range of researchers

46. Template
Conversational in nature with prompts
Room for open ended responses
About the researcher NOT the library

47. Effectiveness
Associates library with data
Helps librarians understand the language and perceptions of researchers
Led to:
● New training opportunities
● Better context and understanding when communicating with researchers about
their data
● New strategies for developing library services and resources

48. Data Series

49. Why a data series?
● Creates/strengthens partnership with data expertise across institution
● Wider range of classes draws more attention to library classes
● Focus marketing efforts

50. How/who we’ve partnered with
● Institute for Innovations in Medical Education
● Department of Population Health
● College of Nursing
● Medical Center IT
● DataCore
● Main Campus Library Data Services

51. Effectiveness
Associates library with data
Bigger presence than library can achieve on its own
Gives the library time to develop more courses

52. Summer 2016
DDTD
Fall 2016
DDTD
Spring 2017
DDTD
REDCap Consults and Workshops

53. Data
Management
Training
@ NYU Langone

54. Data
Management
Training
@ NYU Langone
Informationist
Grants
Lab
Management
Tool

55. Data
Management
Training
Data
Interviews
@ NYU Langone

56. Data
Management
Training
Data
Consult
Service
1-credit
Graduate
Course
Data
Series
@ NYU Langone

57. Data
Management
Training
Data
Consult
Service
1-credit
Graduate
Course
Data
Series
NIH BD2K
Grant
NNLM
Pilot
Program
@ NYU Langone Health Sciences
Library Community

58. Questions?
kevin.read@med.nyu.edu
alisa.surkis@med.nyu.edu