This presentation was presented to the faculty librarians and staff at the George A. Smathers Libraries - University of Florida as part of a faculty candidate presentation campus interview.

1. Vision
for
an
academic
research
library
as
partner
in
campus-­‐wide
data
management
as
it
contributes
to
a
preeminent
ins8tu8on
Plato
L.
Smith
II,
CLIR/DLF
Postdoc
Fellow
at
UNM
University
of
Florida
Libraries
August
25,
2015

2. As
We
May
Think
“A
record
[data/database]
if
it
is
to
be
useful
to
science,
must
be
con8nuously
extended,
it
must
be
stored,
and
above
all
it
must
be
consulted.”
–
Vannevar
Bush,
1945
“The
process
by
which
data
is
captured
and
maintained
con8nues
to
evolve
and
mature
as
scien8fic
needs
change.”
–
DAF
Interview
P1
Par8cipant
(2013)
q How
can
an
Academic
Research
Library
(ARL)
make
people,
research,
and
data
management
services
be^er?
8/25/2015
Plato
L.
Smith
II
2

3. Table
of
Contents
1. An
Academic
Research
Library
Perspec8ve
2. A
Data
Assessment
Framework
Use
Case
3. Academic
Research
Library
as
Broker
4. An
Organiza8onal
Approach
–
UF
5. Address
Other
RDM
Challenges
6. Build
Collabora8on,
Engagement,
&
Support
8/25/2015
Plato
L.
Smith
II
3

4. An
Academic
Research
Library
Perspec@ve
1. CCSDS
OAIS
Reference
Model
(2002)
–
ISO14721:2003
2. Levels
1
–
3
cura8on
(2003)
3. Data
Cura8on
Centre
–
DCC
(2004)
4. DCC
Cura8on
Lifecycle
Model
(2007)
5. NSF
DMP
Requirement
(2011)
6. JISC
Research
Lifecycle
Model
(2013)
7. OSTP
Memo
(2013)
8. NSF
Public
Access
Plan
(2015)
Map
Research
Data
Life
Cycle
to
Domains
via
UF
RDMS
Source:
UF
Libraries
Research
Data
Management
Support
(RDMS)
8/25/2015
Plato
L.
Smith
II
4

5. A
Data
Asset
Framework
Use
Case
• Data
Assess
Framework
(DAF)
Methodology
• Mixed
Methods
–
surveys
and
interviews
• Data
Assessment
(Environmental
Scan)
• Gap
Analysis
• Mul8ple
Research
Labs
Data
Assets
DAF
Types
Sources
The
DAF
was
developed
in
2009
by
the
Humani8es
Advanced
Technology
and
Informa8on
Ins8tute
(HATII),
University
of
Glasgow
in
conjunc8on
with
the
DCC
via
JISC
support.
8/25/2015
Plato
L.
Smith
II
5

6. A
Data
Asset
Framework
Use
Case
Research
Labs/Centers
@FSU
Ø Labs/Centers
–
6/58
(10%)
1. Center
for
Ocean-­‐Atmospheric
Predic8on
Studies
(COAPS)
2. Na8onal
High
Magne8c
Field
Laboratory
(NHMFL)
3. Marine
Coastal
Laboratory
4. Antarc8c
Marine
Geology
Research
Facility
(AMGRF)
5. Center
for
Advanced
Power
Systems
(CAPS)
6. Geophysical
Fluid
Dynamics
Ins8tute
(GFDI)
Ø Interdisciplinary
Ø Mul8disciplinary
Scien@sts/Faculty
Par@cipa@on
Ø Direct
email
to
Directors
Ø Distributed
to
domain-­‐
specific
list
serves
(Purposive
Sampling)
Ø Responses
and
Comple8on
– Surveys
–
107/129
(83%)
– Interviews
–
7/6
(86%)
8/25/2015
Plato
L.
Smith
II
6

7. 23
29
26
3
3
10
7
0
5
10
15
20
25
30
35
Senior
Researcher
Principal
Inves@gator
Research
Assistant
Research
Technician
Research
Support
Research
Student
Other
What
is
your
primary
research
role?
A
Data
Asset
Framework
Use
Case
8/25/2015
Plato
L.
Smith
II
7

8. A
Data
Asset
Framework
Use
Case
20
17
16
8
70
6
0
20
40
60
80
Project
manager
Research
assistant
Research
groups
Na@onal
data
center
You
Other
Who
is
responsible
for
managing
your
research
data
(select
all
that
apply)?
RDM
Responsibility
8/25/2015
Plato
L.
Smith
II
8

9. A
Data
Asset
Framework
Use
Case
3
48
58
74
42
26
2
0
10
20
30
40
50
60
70
80
What
is
the
data
type
of
your
primary
data?
Primary
Data
Type
8/25/2015
Plato
L.
Smith
II
9

10. A
Data
Asset
Framework
Use
Case
1
37
43
50
3
9
46
12
23
40
6
30
31
4
6
4
9
2
0
10
20
30
40
50
60
Audio
tapes
Computer
soYware
Data
-­‐
computer
Data
-­‐
sensors
Digital
audio
files
Digital
video
files
Excel
sheets
Fieldwork
data
Images,
scans,
photos
Laboratory
notes
MS
Access
MS
Powerpoint
MS
Word
Slides
-­‐
physical
media
SPSS
files/sta@s@cal
Video
tapes
Websites
Other
What
is
the
data
type
of
your
secondary
data?
Secondary
Data
Type
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Plato
L.
Smith
II
10

11. A
Data
Asset
Framework
Use
Case
50
54
29
6
4
45
18
6
0
10
20
30
40
50
60
Finding
files/folder
structure
Loca@ng
where
data
files
are
stored
Non
standard
file
formats
Legal
issues
arising
from
transfer
of
Problems
establishing
ownership
of
Finding
or
accessing
research
data
Security
and
protec@on
of
files
Other
Which
of
the
following
data
management
issues
have
you
experienced?
[Please
select
all
that
apply]
RDM
Issues
8/25/2015
Plato
L.
Smith
II
11

12. A
Data
Asset
Framework
Use
Case
14
15
49
68
30
24
5
32
7
0
10
20
30
40
50
60
70
80
CD/DVD
External
commercial
web
data
storage
External
Hard
Disk
Local
computer
My
documents
on
research
lab
PC
Paper/file
records
Technology
vendor
file
server
Other
provided
file
server
Other
-­‐
give
details
Where
do
you
store
your
data
(excluding
backup
copies)?
[Select
all
that
apply]
8/25/2015
Plato
L.
Smith
II
12

13. A
Data
Asset
Framework
Use
Case
Budget/funding
22%
Infrastructure/
resources
31%
Stakeholders
8%
Storage/
technology
25%
Other
14%
What
are
some
barriers
for
you
with
regards
to
managing
and
storing
your
research
data?
Budget/funding
Infrastructure/resources
Stakeholders
Storage/technology
Other
8/25/2015
Plato
L.
Smith
II
13

14. Academic
Research
Library
as
Broker
• Capaci8es/Facili8es
• Infrastructure
(HPC)
• Resources
&
Tools
• Library
&
Campus-­‐
wide
stakeholders
• University,
Government,
Industry
• Research
Data
Management
(RDM)
• Repository
(IR@UF)
• Publishing/Sharing
• Data
Management
Planning
(DMP)
• Research
Data
Lifecycle
• DMP
Tools
Plan
Access
Assets
Support
8/25/2015
Plato
L.
Smith
II
14

15. Academic
Research
Library
as
Broker
1. Conduct
Data
Assessment
&
Gap
Analysis
across
mul8ple
disciplines,
ins8tutes,
and
centers
(e.g.
DAF,
Evalua8on,
Monitor
&
Track
Metrics)
2. Ar@culate
and
facilitate
Federal
Data
Access
Policies
(e.g.
NSF,
OSTP)
compliance
–
educa8on,
IM,
outreach,
training,
webinars,
workshops
3. Assist
faculty
with
Data
Management
Planning
(DMP)
throughout
research
data
lifecycle
–
DMP
Tool,
IR@UF,
HiPerGator
(HPC),
FSP
FAQ
4. Connect
and
integrate
with
diverse
communi8es
of
prac8ce
(e.g.
USGS)
5. Document
Outcomes,
Metrics,
&
Successes
(e.g.
varied
infographics,
IM)
6. Leverage
services
and
services
realloca8on
(e.g.
data
storage,
HPC)
7. Secure
library,
campus,
consor8um,
and
university
support
(e.g.
GUIRR)
8/25/2015
Plato
L.
Smith
II
15

16. (Diagram
modeled
aoer
Purdue
Libraries
-­‐
used
with
permission)
8/25/2015
Plato
L.
Smith
II
16

17. (Diagram
modeled
aoer
Purdue
Libraries
-­‐
used
with
permission)
Promote
cross-­‐
cupng
DMP/
RDM
educa8on,
outreach,
and
training
synergies
8/25/2015
Plato
L.
Smith
II
17

18. Address
Other
RDM
Challenges
q Earth-­‐Centered
Communica8on
for
Cyberinfrastructure
(EC3)
2015
Field
Trip
Scenario
q Metadata,
Features/Func8onality,
Architecture,
Best
Prac8ces,
Standards
q Interoperability,
Data
Collec8on
&
Integra8on,
Seman8cs
(e.g.
ontology,
vocabulary)
q Applica8ons,
Web
Services
(e.g.
APIs,
W3C,
SOAP,
RESTful,
etc.)
q End-­‐to-­‐End
development
(e.g.
funding
beyond
prototype/end
of
funding)
Diagram
developed
by
GIS
specialist,
Nicole
Kong
(used
with
permission)
8/25/2015
Plato
L.
Smith
II
18

19. Address
Other
RDM
Challenges
USGS
Community
for
Data
Integra8on
(CDI)
Science
Support
Framework
(SSF)
–
2015
8/25/2015
Plato
L.
Smith
II
19

20. Address
Other
RDM
Challenges
General
and
Domain
Specific
Repositories
• dLOC-­‐UFDC,
Dryad,
DataVerse,
Figshare,
HathiTrust,
IR@UF
• EarthChem,
GenBank,
idigBio,
Integrated
Earth
Data
Applica8ons
(IEDA)
•
arXiv.org,
XSEDE,
Long
Term
Ecological
Research
(LTER),
Morphbank,
NCBI,
NGDC/NOAA,
NODC/NOAA,
UCAR/NCAR
General
and
Domain
Specific
Tools
• DataUp,
dataZoa,
DCC
Tools,
iPython
Notebook,
Visual
Understanding
Environment
(VUE)
• Digital
Research
Tools
(DIRT),
import
io,
LabArchives,
MATLAB,
OPENRefine,
R,
SPSS,
Tabula
• FGDC
tools,
NCBI
(APIs,
Code
Libraries,
Data
Formats,
GitHub
repository),
PubMed
Tools
Author
disambigua8on
and
linked
data
Linking
• ORCiD,
DOI,
EZ-­‐ID,
Zenodo
• Impactstory,
Open
Science
Framework
(OSF),
VIVO
• Linked
Open
Data
(5
star),
Ontologies,
W3C
Prov,
RDF,
XML
8/25/2015
Plato
L.
Smith
II
20

21. Address
Other
RDM
Challenges
8/25/2015
Plato
L.
Smith
II
21

22. Build
Collabora8on,
Engagement,
&
Support
q Build
and
extend
exis8ng
collabora8ons
and
partnerships
q Develop
Data
Management
Use
Cases
and
RDM
Scenarios
q Engage
UF
Preeminence
Faculty
(e.g.
8
Preeminence
areas
of
focus
–
4
CoE,
3
CoLAS,
3
CoM,
1
CoBA,
1
Levin
CoL,
1
CoN,
1
CoP,
1
CoPH&HP)
q Engage
Communi8es
of
Prac8ces
-­‐
AGU,
ARL
SHARE,
CUAHSI,
Dataverse,
DataONE,
Deep-­‐C,
Dryad,
EarthCube,
ESIP,
GoMRI,
GreyNet,
HASTAC,
IDCC,
iDigBio,
NHMFL,
OGC,
RDA,
USGS
q Develop
new
Partnerships
and
Funding
Opportuni8es
(e.g.
UF
Division
of
Research
Program
Development,
COS,
NSF
Funding)
8/25/2015
Plato
L.
Smith
II
22

23. Build
Collabora8on,
Engagement,
&
Support
q Computer
and
Informa@on
Science
and
Engineering
(CISE)
Research
Ini@a@on
Ini@a@ve
(CRII)
–
untenured
faculty/1st
2yr
of
academic
posi8on
aoer
PhD
–
Solicita8on
#15-­‐569
q CISE
Research
Infrastructure
(CRI)
–
Community
Infrastructure/enhancement
of
exis8ng
CI-­‐EN
-­‐
Solicita8on
#15-­‐590
q Campus
Cyberinfrastructure
–
Data,
Networking,
and
Innova@on
Program
(CC*DNI)
–
(1)
DIBBs
(Mul8-­‐campus
Model)
or
(2)
Data
Driven
Networking
Infrastructure
for
the
Campus
Researcher
-­‐
Solicita8on
#15-­‐534
q Grant
Opportuni@es
for
Academic
Liaison
with
Industry
(GOALI)
–
promotes
university-­‐industry
partnerships/linkages
-­‐
Solicita8on
#12-­‐513
(any8me)
q Industry/University
Coopera@ve
Research
Centers
Program
(I/UCRC)
–
develops
long-­‐term
partnerships
among
industry,
academe,
and
government
–
Solicita8on
#13-­‐594
8/25/2015
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L.
Smith
II
23

24. References
q ACRL.
(2015).
Informa8on
Literacy
Competency
Standards
for
Higher
Educa8on.
Retrieved
August
19,
2015
from
ACRL
ILCS.
q Brandt,
D.
S.
(2015)
DLF
E-­‐Research
Network
2015
Webinar
on
“Introduc8on/
Research
Data
Management
Services
in
Academic
Libraries”
for
2015
DLF
E-­‐
Research
Network
Cohort,
May
13,
2015.
q CCSDS.
(2002).
Consulta8ve
Commi^ee
for
Space
Data
Systems
(CCSDS)
The
OAIS
Reference
Model.
Retrieved
August
19,
2015
from
OAIS.
q Mar8n,
J.
(2002).
Cultures
in
Organiza8ons:
Three
Perspec8ves.
Oxford
University
Press.
q NSF.
(2015).
NSF’s
Public
Access
Plan:
Today’s
Data,
Tomorrow’s
Discoveries
–
Increasing
Access
to
the
Results
of
Research
Funded
by
the
Na8onal
Science
founda8on.
Retrieved
August
19,
2015
from
h^p://www.nsf.gov/pubs/2015/nsf15052/nsf15052.pdf.
q UF
Libraries.
(2015).
Research
Data
Management
Support
(RDMS).
q USGS.
(2015).
USGS
Community
for
Data
Integra8on.
The
CDI
Science
Support
Framework
(SSF).
Retrieved
August
19,
2015
from
h^p://www.usgs.gov/cdi/about.html.
q USGS.
(2015).
USGS
Fundamental
Science
Prac8ces
(FSP).
Retrieved
August
19,
2015
from
h^p://www.usgs.gov/fsp/.
8/25/2015
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L.
Smith
II
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25. Acknowledgements
1. UF
Libraries
Data
Management
Librarian
Search
Commi^ee
2. Brian
Keith,
Hannah
Norton,
Laurie
Taylor,
Tina
Marie
Litchfield
3. FSU
School
of
Informa8on
(Florida's
iSchool)
4. Dr.
Paul
Marty
and
Dr.
A.K.S.K.
Prasad
(FSU)
5. CLIR/DLF
Postdoctoral
Program
6. University
of
New
Mexico
Libraries
7. Dr.
Karl
Benedict
(UNM)
8. Sco^
D.
Brandt
(Purdue)
9. New
Mexico
EPSCoR
10. NSF-­‐Funded
EarthCube,
EC3,
and
DataONE
Projects
11. USGS
Community
for
Data
Integra8on
(CDI)/Fundamental
Science
Prac8ces
(FSP)
publicly-­‐available
resources
8/25/2015
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L.
Smith
II
25

26. Thank
you
Ques8ons
and
comments
Crea8ve
Commons
A^ribu8on-­‐NonCommercial
4.0
Interna8onal
License
8/25/2015
Plato
L.
Smith
II
26