Presentation for Northwestern University's first Computational Research Day, April 22, 2014. http://www.it.northwestern.edu/research/about/campus-events/research-day/agenda.html . By Cunera Buys, e-Science Librarian, and Claire Stewart, Director, Center for Scholarly Communication and Digital Curation and Head, Digital Collections

1. Research
Data
Management:
How
will
Northwestern
address
new
sharing
requirements?
Cunera
Buys
Claire
Stewart

2. FUNDING
AGENCIES

3. • Issued
February
22,
2013
by
the
White
House
Office
of
Science
and
Technology
Policy
(OSTP).
• GranNng
agencies
must
develop
a
plan
to
make
the
results
of
federally-­‐funded
research
publically
available
free
of
charge
within
12
months
aTer
original
publicaNon.
• Affects
granNng
agencies
with
more
than
$100
million
R&D
expenditures.
• Includes
published
arNcles
and
data.
hZp://www.whitehouse.gov/sites/default/files/
microsites/ostp/
ostp_public_access_memo_2013.pdf
OSTP
MEMORANDUM

4. OSTP
Update
• Follow
Up
Memorandum
issued
on
March
24,
2014
by
John
Holdren
• hZp://www.whitehouse.gov/sites/default/files/microsites/ostp/
OpenAccess_March-­‐2014.pdf

5. Responding
Agencies
• Department
of
Health
and
Human
Services
(HHS)
• Agency
for
Healthcare
Research
and
Quality
(AHRQ)
• HHS
Office
of
the
Assistant
Secretary
for
Preparedness
and
Response
(ASPR)
• Centers
for
Disease
Control
and
PrevenNon
(CDC)
• Department
of
Homeland
Security
(DHS)
• Department
of
Defense
(DoD);
• Department
of
Energy
(DOE)
• Department
of
the
Interior
(DOI)
• Department
of
TransportaNon
(DOT)
• Department
of
EducaNon
(ED)
• Environmental
ProtecNon
Agency
(EPA)
• Food
and
Drug
AdministraNon
(FDA)
• NaNonal
AeronauNcs
and
Space
AdministraNon
(NASA)
• NaNonal
InsNtutes
of
Health
(NIH)
• Department
of
Commerce
(DOC)
• NaNonal
InsNtute
of
Standards
and
Technology
(NIST)
• NaNonal
Oceanic
and
Atmospheric
AdministraNon
(NOAA)
• NaNonal
Science
FoundaNon
(NSF)
• Office
of
the
Director
of
NaNonal
Intelligence
(ODNI)
• Smithsonian
InsNtuNon
(SI)
• United
States
Agency
for
InternaNonal
Development
(USAID)
• United
States
Department
of
Agriculture
(USDA)
• United
States
Department
of
Veterans
Affairs
(VA).

6. Agency
Proposals
• Agency
plans
include
a
variety
of
approaches
• use
NIH’s
PubMedCentral
infrastructure
• Develop
public-­‐private
partnerships
• Create
their
own
database
• UNlize
exisNng
agency
infrastructure

7. Current
status
• Agencies
have
submiZed
plans
• Plans
have
been
reviewed
by
OSTP
• OSTP
has
commented
and
returned
plans
to
agencies
• Agencies
are
currently
revising
plans
to
address
comments
• OSTP
will
convene
interagency
meeNngs
–
will
allow
agencies
to
work
together
to
refine
plans
and
explore
other
ways
to
collaborate

8. Why
do
funders
and
broader
science
community
want
to
share
and
preserve
data?

9. Prevent
Data
Loss

10. ScienNfic
Reproducibility

12. RecogniNon
Chapter
II.C.2.f(i)(c),
Biographical
Sketch(es),
has
been
revised
to
rename
the
“PublicaNons”
secNon
to
“Products”
and
amend
terminology
and
instrucNons
accordingly.
This
change
makes
clear
that
products
may
include,
but
are
not
limited
to,
publicaNons,
data
sets,
soTware,
patents,
and
copyrights.

13. Other
reasons
to
manage
and
share
your
data
• saves
you
Nme
• increases
the
impact
of
your
research
through
data
citaNon.
• clearly
documents
and
provides
evidence
for
your
research
in
conjuncNon
with
published
results.
• meet
copyright
and
ethical
compliance
(ie.
HIPAA).
• preserves
data
for
long-­‐term
access
and
prevents
loss
of
data.
• describes
and
shares
data
with
others
to
further
new
discoveries
and
research.
Adapted
From:
University
of
Minnesota
Libraries
Data
Management
web
page:
hZps://www.lib.umn.edu/datamanagement

14. Data
Management
Survey
• A
joint
project
by
E-­‐Science
Working
group:
• Northwestern
University
Libraries
• Northwestern
University
InformaNon
Technology
• Office
for
Sponsored
Research
• Weinberg
College
of
Arts
and
Sciences
• Faculty,
graduate
students,
post
docs,
selected
staff
on
both
campuses
• 831
responses
and
788
completed
the
survey
• Approximately
1/3
faculty
and
postdocs,
1/3
staff
and
1/3
graduate
students

15. Data
Management
Survey
Types
of
quesNons
• Types
and
size
of
data
• How
data
is
stored
• Data
sharing
• Data
retenNon
• Data
management
planning
• Training
or
assistance
needed

16. Data
Management
Survey
Preliminary
results
• Most
common
data
types
and
sizes
• Spreadsheets
and
Structured
data
(.csv,
.dat,
.xml)
•
text
• images
• 1-­‐500
GB
storage
needs

17. Data
Management
Survey
Preliminary
results
• Data
storage
• PC
hard
Drive
• Departmental/
School
Server
• Internet
based
services
(e.g.
Dropbox)

18. Data
Management
Survey
Preliminary
results
• Data
retenNon
and
preservaNon
• 5-­‐10
years
• Indefinitely
#
QuesNon
Less
than
1
year
1-­‐5
years
5-­‐10
years
More
than
10
years
Indefinitely
Don’t
know
Total
Responses
1
Source
material/
Raw
Data
16
133
162
52
181
100
644
2
Processed
Data
8
115
164
60
164
119
630
3
Results
of
StaNsNcally
Manipulated
Data
6
107
158
53
154
149
627
4
Published
Data
9
87
119
60
230
126
631
Totals
39
442
603
225
729
494
2532

19. Data
Management
Survey
Preliminary
results
• Data
Sharing
• Most
plan
to
share
their
data
• Before
publicaNon
will
share
data
with
colleagues
at
Northwestern
or
within
research
group
• ATer
publicaNon
• Colleagues
in
field
(inside
and
outside
NU)
• Public
at
large

20. Data
Management
Survey
Preliminary
results
• Would
you
be
willing
to
parNcipate
in
a
follow-­‐up
interview
regarding
research
data
management?
• 213
“yes”
but
…..
• Please
contact
us!

22. Responses:
Funders,
ScienNsts

23. Publisher
responses

24. Deposit
on
publicaNon
of
arNcle
• Some
Journal
publishers
require
or
recommend
that
supporNng
data
for
arNcles
be
made
publicly
available.
• The
Joint
Data
Archiving
Policy
(JDAP)
requires
data
sharing
in
a
public
archive
as
a
condiNon
of
publicaNon.
– Journals
that
have
adopted
JDAP
include:
Science,
Nature
and
GeneNcs
• The
author
is
usually
responsible
for
making
data
available
in
repository/
archive.
• Check
data
archiving
policies
of
journals
before
submivng
arNcles.

25. Journal
Requirements
7.
Sharing
of
Data,
Materials,
and
SoTware
PublicaNon
is
condiNonal
upon
the
agreement
of
the
authors
to
make
freely
available
any
materials
and
informaNon
described
in
their
publicaNon
that
may
be
reasonably
requested
by
others.
Data
Availability
PLOS
journals
require
authors
to
make
all
data
underlying
the
findings
described
in
their
manuscript
fully
available
without
restricNon,
with
rare
excepNon1.
When
submivng
a
manuscript
online,
authors
must
provide
a
Data
Availability
Statement
describing
compliance
with
PLOS's
policy.
If
the
arNcle
is
accepted
for
publicaNon,
the
data
availability
statement
will
be
published
as
part
of
the
final
arNcle.
Refusal
to
share
data
and
related
metadata
and
methods
in
accordance
with
this
policy
will
be
grounds
for
rejecNon.
PLOS
journal
editors
encourage
researchers
to
contact
them
if
they
encounter
difficulNes
in
obtaining
data
from
arNcles
published
in
PLOS
journals.
If
restricNons
on
access
to
data
come
to
light
aTer
publicaNon,
we
reserve
the
right
to
post
a
correcNon,
to
contact
the
authors'
insNtuNons
and
funders,
or
in
extreme
cases
to
retract
the
publicaNon.

26. Rise/growth
of
data
journals

27. Academic
community
response

28. Academic
community
response

29. Academic
community
response

30. Library
response
• Stewardship,
insNtuNonal
memory
• Long
tradiNon
of
broad
subject
experNse,
liaisons
to
and
in
every
discipline
• Data
services:
finding
data,
licensing
data,
deposiNng
data,
soTware
for
working
with
data
• Historical
strengths
in
areas
important
for
data
curaNon:
organizaNon
of
informaNon,
intellectual
descripNon,
rights
expression,
deposit,
preservaNon,
citaNon
• NU
Library
possible
models:
– Support
for
data
management
plan
development
(already
doing)
– Data
concierge
(partly
doing)
– Extend
repository
services
for
data
(small
data
only?,
pilot
in
dev)
– Embedded
data
librarians
(what
would
this
cost?
)

31. Discussion
• What
concerns
you
about
mandates
for
data
sharing?
• What
are
the
norms
for
research
data
sharing
in
your
discipline?
• How
are
you
staffing
and
funding
research
data
management
in
your
group?
• What
addiNonal
training
or
support
would
be
valuable?

32. RESOURCES:
• Northwestern
University
Library
Data
Management
Web
Page:
hZp://www.library.northwestern.edu/dmp
• DMPTool:
hZps://dmp.cdlib.org/
• Northwestern
University's
Research
Data:
Ownership,
RetenNon
and
Access
Policy:
hZp://www.research.northwestern.edu/policies/documents/research_data.pdf
• Northwestern
University
Library's
Center
for
Scholarly
CommunicaNon
&
Digital
CuraNon:
• hZp://www.library.northwestern.edu/services/faculty-­‐graduate-­‐students/
scholarly-­‐communicaNon
• Cunera
Buys-­‐
e-­‐science
librarian:
c-­‐buys@northwestern.edu

33. Image Credits
Title
slide:
Work
found
at
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(hZps://creaNvecommons.org/licenses/by-­‐sa/2.0/)
Slide
16
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