Presentation given at the Indiana University School of Medicine's Ruth Lilly Medical Library. Contains information and resources specific to Indiana University Purdue University Indianapolis (IUPUI). For full class materials, see LYD17_IUPUIWorkshop folder here: https://osf.io/r8tht/.

1. Love Your Data (LYD)
Locally
14 February 2017
Medical Library, IB-226

2. Hello!
Heather Coates (MS,
MLS)
Digital Scholarship &
Data Management Librarian
Erin Foster (MSLS)
Data Services Librarian

3. Love Your Data
week
February 13-17, 2017
loveyourdata.wordpress.com
#LYD17 #loveyourdata
#WhyILYD17

4. ‘Data quality’ is this year’s theme

5. 1.
Why are we here?
Snacks?

10. 2.
What can the library
do for you?
We’re here to help!

11. Individual consults
Workshops & classes
Training & education
• Data management & sharing plans
• Data sharing & reuse
• Open science/research tools
Library data services

12. What do you want
to know?
Take a look at the Topic Menu!

13. “
Why does good data management
matter?

14. Some realities…

15. Reproducibility in science

16. “
The publisher says I have to make
my data available before the article
can go to press. How do I do that?

17. Data sharing -– who’s asking? (1)

18. Data sharing -- who’s asking? (2)
Vasilevsky NA, Minnier J, Haendel MA, Champieux RE. (2016) Reproducible and reusable research: Are journal data sharing policies
meeting the mark? PeerJ Preprints 4:e2588v1 https://doi.org/10.7287/peerj.preprints.2588v1
Review of 318 biomedical journals’ author
instructions & editorial policies around data
sharing

19. Data sharing –- share where?
Publisher sites
Subject repositories
• NCBI databases (e.g., GenBank, dbGaP)
• ICPSR
• Roper Center
• Odum Institute
• DataDryad
Institutional repositories
• IUPUI DataWorks

20. Data sharing -- considerations
Mechanism Sharing
Long-term
access
Metrics
Publisher sites  ? ?
Subject
repositories
  ?
DataWorks   
Scholarly Data
Archive (SDA)
X  X

21. Data sharing -- support @ IUPUI
IUPUI DataWorks - a repository for sharing and
preserving digital research data
Scholarly Data Archive (SDA) - a
distributed, tape system for storing and accessing
research data
Library help?
• Gathering, documenting data for deposit
• Guidance around deposit process into DataWorks or
SDA

22. “
What is a data management plan
(DMP)? Why would I need one?

23. The purpose of data
management planning is to ensure that
research data produced by a project are
high quality, well organized,
thoroughly documented,
preserved, and accessible so that the
validity of the data can be determined at
any time.

24. DMPs -- the basics
Describe what you will do with your data during
and after the proposed project.
Ensure data is safe now and in the future.
A DMP should reflect:
• awareness of data management and curation in
your discipline.
• a feasible plan to utilize available
cyberinfrastructure.
(try to…)
• explain the rationale for your choices.
• identify roles for data management and sharing
activities.

25. DMPs -- the pieces
Common elements include:
• Types of data
• Standards and metadata
• Access and sharing
• Re-use, re-distribution, and the production of
derivatives
• Long-term preservation
• Budget*

26. “
How do I avoid losing data? What
systems are available to store and
backup research data?

27. Storage & backup -- the 3-2-1 rule

28. Storage & backup -- create master files
Identify transformative steps in your data workflow
a) Raw data
b) Recoded or derived data
c) Screened, cleaned, or processed data
d) Subsets for manuscripts
Save a copy and archive it before each key
transformation
Document each master file with a README
file…plus any other study and data documentation
that might be helpful

29. Storage & backup -- IUPUI systems
Active storage: files that continue to be
modified, worked on
• Box @ IU [entrusted & health data accounts
available]: a cloud based, file sharing and storage
option
Archival storage: final versions, long-term
storage
• Scholarly Data Archive (SDA): a distributed,
tape system for storing and accessing research
data

30. “
Help! I need help creating and
organizing good documentation for
my project.

31. Documentation
is a love letter
to your data

32. Documenting, describing, defining
Capture crucial details needed for post
publication peer review and validation of
results, such as:
• Research questions/aims
• IRB protocol
• Informed
consents/authorizations
• Funding sources
• Study personnel
• Protocol deviations
• Data collection
instruments or tools
• Data sources
• Data collection process
or workflow

33. README files
What is it?
A file that includes
information about other
files in a directory.
Generally is:
• Simple
• Short
• Descriptive
• Instructive
Key features:
Authors
Citation
Data description
• Collection dates
• GeoSpatial
• Directory & file
name conventions
• Changelog
File information
Access & sharing

34. “
Where can I learn about software
and tools available at IUPUI?

35. IUPUI tools & resources
DMPTool
Box*
REDCap*
Research Data
Complex (RDC)
Git/GitHub
R & RStudio
IUanyWare
Computing*
■ Karst
■ Big Red II
Storage*
■ Scholarly Data
Archive (SDA)
IUPUI DataWorks
*Office hours and/or trainings available

36. 3.
Upcoming events
Coming to an IUPUI
location near you!

37. Data Bootcamp
A set of trainings on commonly used software/tools
(e.g., RStudio, GitHub, OpenRefine), data
encryption methods, and open research practices.
Spring 2017

38. Data
visualization
series
A series of workshops focused on visualizing
data in basic, clinical, and applied science.
Summer 2017

39. Human
subjects data
workshop
A workshop on the handling of human subjects
data – from systems (what does HIPAA aligned
mean?!) to data de-identification
methods/techniques.
Fall 2017

40. What would
you like to
see?

41. Credits
Special thanks to all the people who made and
released these awesome resources for free:
■ Presentation template by SlidesCarnival
■ Icons by Noun Project:
Created by Pravin Unagar (slide 11/top), Gerald
Wildmoser (slide 11/middle), Marina Pla (slide 11/bottom),
and Christine Hanna (slide 38)
■ Image courtesy of xkcd (slide 37)
Extra thanks:
■ Love Your Data 2017 planning committee
■ Jennifer Herron and RLML 3D print team

42. Thanks!
Any questions?
You can find us at:
medlref@iupui.edu
ulib.iupui.edu/form/info_request