This presentation by Sheila Corrall was given at the Scholarly Communication and Research Infrastructures Steering Committee Workshop. The workshop title was Libraries and Research Data Management – What Works?

1. Immersive
Informa-cs
Educa-on
for
Research
Data
Specialists
Sheila
Corrall
Professor
and
Chair
Library
&
Informa-on
Science
www.ischool.piA.edu/lis

2. Digital
Cura-on
Educa-on
in
the
USA
• Massive
investment
in
RDM
educa-on
and
capacity
building
by
Ins-tute
of
Museum
&
Library
Studies
– $9M
on
curriculum
development,
scholarships,
etc.
• Around
33%
of
US
schools
offer
one
or
more
courses
– 10
special
tracks,
7
Master’s
programs,
4
cer-ficates
– target
audiences
include
LIS
Master’s
and
PhD
students,
exis-ng
prac--oners
and
graduates
in
other
disciplines
– experien-al
learning
via
internships
and
field
experiences
• Other
ini-a-ves
include
annual
training
ins-tutes
and
library-­‐led
data
literacy
for
Sci
&
Eng
students
(Corrall,
2012;
Corrall,
Kennan
&
Afzal,
2013)

3. Family
of
Data
Scien-st
Roles
• Data
engineer
–
focus
on
so_ware
development,
coding,
programming,
tools
• Data
analyst
–
focus
on
business/scien-fic
analy-cs
and
sta-s-cs,
e.g.,
R,
SAS,
Excel,
to
support
researchers
and
modelers,
business
• Data
librarian
–
focus
on
advocacy,
research
data
management/informa-cs
in
a
university/ins-tute
• Data
steward
–
focus
on
long
term
digital
preserva-on,
repositories,
archives,
data
centers
• Data
journalist
–
focus
on
telling
stories
and
news
(Lyon,
2012)

4. Re-­‐engineering
Libraries
Re-­‐skilling
Librarians
• New
prac-ce
modes
– from
liaison
to
immersive
immersiveInforma-cs
– co-­‐developed
by
UKOLN,
University
of
Bath
and
University
of
Melbourne
• Immersive
sessions
in
lab
(Lyon,
2012)

5. RDM
Seminar
@
PiA
iSchool
Course
Developer
and
Instructor:
Dr.
Liz
Lyon
1. Introduc-ons
and
Overview
2. Data
Landscape
3. Ins-tu-ons
and
Data
4. Data
Requirements
and
Capability
5. Roadmaps,
Strategy
and
Planning
6. Data
Management
Plans
7. Disciplinary
Data
1
8. Immersive
Analysis
with
Faculty
Researchers
9. Legal
and
Ethical
Issues
10. Disciplinary
Data
2
11. Data
Centers
12. Data
Advocacy,
Skills,
Training
13. Data
Sustainability
and
Costs
14. Roadmap
Presenta-ons
Spring
2014,
Fall
2014

6. Pt.
2
Research
Data
Infrastructures
Course
Developer
and
Instructor:
Dr.
Liz
Lyon
1. Introduc-ons
and
Overview
2. Data
Standards
3. Data
Cita-on
and
Metrics
4. Data
Publica-on
5. Data
Discovery
6. Immersive
Session
with
Researchers
7. Disciplinary
Data
3
8. Data
Storage
9. Data
Repositories
10. Data
Preserva-on
(Long-­‐term)
11. Ci-zen
Science,
Ci-zen
Data
12. Data
Science
13. Data,
Society,
Futures
14. Presenta-ons
and
Summary
Evalua-on
Fall
2014,
Spring
2015

7. 1. Briefing
paper
on
developing
a
university
data
policy
2. Cri-cal
appraisal
of
selected
data
tools
for
data
audits
and
data
management
plans
3. Disciplinary
posi-on
paper
4. Develop
an
RDM
Roadmap
or
Business
Case
Presenta-on
(for
a
professional
audience)
with
suppor-ng
evidence
and
documenta-on
?
RDM
Assignments

8. 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
prac-cal
and
illuminated
some
of
the
struggles
that
one
may
encounter
in
discussing
data
as
its
own
area
of
research.”
Course
Features
• Case
studies
and
global
exemplars
• Methodologies
and
tools
• Invited
speakers
• Prepare
for
prac-ce
• Disciplinary
data
focus
• Innova-ve
immersive
session
in
the
lab

9. Sample
MLIS
RDM
Track
Course
Planner
Core/Founda+onal
Courses
(required)
• Understanding
Informa-on
• Library
and
Archival
Compu-ng
• Organizing
and
Retrieving
Informa-on
• Managing
and
Leading
LIS
Specializa+on
Courses
(recommended)
• Research
Data
Management
• Research
Data
Infrastructures
• Informa-on
Architecture
• Metadata
• Data
and
Informa-on
Visualiza-on
Suggested
Elec+ves
(choose
3
or
more)
• Academic
Libraries
• Research
Methods
• Scholarly
Communica-on
• Geographic
Informa-on
Systems
• Preserving
Digital
Culture
• Field
Experience
• Individual
Project

10. Other
Specialist
Data
Courses
at
the
PiAsburgh
iSchool
MS
in
Informa-on
Science
Big
Data
Analy-cs
Specializa-on
www.ischool.piA.edu/ist/degrees/
specializa-ons/big-­‐data.php

12. MSIS
Big
Data
Analy-cs
Specializa-on
Pre-­‐requisite
courses
• Programming
• Sta-s-cs
• Mathema-cs
• Data
Structures
• JAVA
Required
courses
• Decision
Analysis
&
Decision
Support
Systems
• Algorithm
Design
• Database
Management
• Advanced
Topics
in
Database
Management
• Data
Analy-cs
+
Two
elec+ves
One
course
from
• Intro
to
Info
Storage
&
Retrieval
• Data
Mining
One
course
from
• Introduc-on
to
Neural
Networks
• Social
Compu-ng
Two
courses
from
• Geospa-al
Informa-on
Systems
• Mobile
GIS
&
Loca-on-­‐Based
Services
• Network
Science
• Informa-on
Visualiza-on
• Security
&
Privacy
• Advanced
Topics
in
GIS
• Network
Performance
• Computer
Networking

13. Ques-ons
and
Comments
Sheila
Corrall
scorrall@piA.edu
Liz
Lyon
elyon@piA.edu