This document provides an overview of the DMPTool, which is an online tool to help researchers create Data Management Plans (DMPs) required by funders like the National Science Foundation. It describes the background of DMPs and their requirements, highlights the key components of a DMP, and introduces the DMPTool as a free and open-source platform to guide users through the DMP creation process with customized templates for different disciplines. The tool aims to help researchers comply with funder mandates in a streamlined way.
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
The DMPTool: A Resource for Data Management Planning
1. DMPTool
for
Data
Management
Plans
Carly
Strasser
University
of
California
Curation
Center
From
Flickr
by
dipster1
California
Digital
Library
17
May
2012
Ÿ
University
of
North
Texas
3. Partnership
between
CDL
|
10
UC
campuses
|
Peer
institutions
Provide
solutions,
services,
resources
for
digital
assets
Pool
&
distribute
diverse
experience,
expertise,
&
resources
4.
5. From
Flickr
by
DW0825
From
Flickr
by
Flickmor
From
Flickr
by
deltaMike
Digital
data
www.woodrow.org
C.
Strasser
Courtesey
of
WHOI
From
Flickr
by
US
Army
Environmental
Command
6. Where
data
end
up
From
Flickr
by
diylibrarian
www
blog.order2disorder.com
From
Flickr
by
csessums
Data
Metadata
From
Flickr
by
csessums
Recreated
from
Klump
et
al.
2006
7. Where
data
end
up
From
Flickr
by
diylibrarian
www
Data
www
Metadata
From
Flickr
by
torkildr
Recreated
from
Klump
et
al.
2006
8. Trends
in
Data
Archiving
Journal
publishers
Joint
Data
Archiving
Agreement
Data
Papers
Ecological
Archives,
Beyond
the
PDF
Funders
Data
management
requirements
9. What
is
a
data
management
plan?
A
document
that
describes
what
you
will
do
with
your
data
during
and
after
you
complete
your
research
Robert
Stadler
installation
from
Flickr
by
Dom
Dada
11. NSF
DMP
Requirements
From
Grant
Proposal
Guidelines:
DMP
supplement
may
include:
1. the
types
of
data,
samples,
physical
collections,
software,
curriculum
materials,
and
other
materials
to
be
produced
in
the
course
of
the
project
2.
the
standards
to
be
used
for
data
and
metadata
format
and
content
(where
existing
standards
are
absent
or
deemed
inadequate,
this
should
be
documented
along
with
any
proposed
solutions
or
remedies)
3.
policies
for
access
and
sharing
including
provisions
for
appropriate
protection
of
privacy,
confidentiality,
security,
intellectual
property,
or
other
rights
or
requirements
4.
policies
and
provisions
for
re-‐use,
re-‐distribution,
and
the
production
of
derivatives
5.
plans
for
archiving
data,
samples,
and
other
research
products,
and
for
preservation
of
access
to
them
12. 1. Types
of
data
&
other
information
• Types
of
data
produced
• Relationship
to
existing
data
• How/when/where
will
the
data
be
captured
or
created?
C.
Strasser
• How
will
the
data
be
processed?
• Quality
assurance
&
quality
control
measures
• Security:
version
control,
backing
up
biology.kenyon.edu
• Who
will
be
responsible
for
data
management
during/after
project?
From
Flickr
by
Lazurite
13. 2. Data
&
metadata
standards
• What
metadata
are
needed
to
make
the
data
meaningful?
• How
will
you
create
or
capture
these
metadata?
Wired.com
• Why
have
you
chosen
particular
standards
and
approaches
for
metadata?
14. 3. Policies
for
access
&
sharing
4. Policies
for
re-‐use
&
re-‐distribution
• Are
you
under
any
obligation
to
share
data?
• How,
when,
&
where
will
you
make
the
data
available?
• What
is
the
process
for
gaining
access
to
the
data?
• Who
owns
the
copyright
and/or
intellectual
property?
• Will
you
retain
rights
before
opening
data
to
wider
use?
How
long?
• Are
permission
restrictions
necessary?
• Embargo
periods
for
political/commercial/patent
reasons?
• Ethical
and
privacy
issues?
• Who
are
the
foreseeable
data
users?
• How
should
your
data
be
cited?
15. 5. Plans
for
archiving
&
preservation
• What
data
will
be
preserved
for
the
long
term?
For
how
long?
• Where
will
data
be
preserved?
• What
data
transformations
need
to
occur
before
preservation?
• What
metadata
will
be
submitted
alongside
the
datasets?
• Who
will
be
responsible
for
preparing
data
for
preservation?
Who
will
be
the
main
contact
person
for
the
archived
data?
From
Flickr
by
theManWhoSurfedTooMuch
16. NSF’s
Vision*
DMPs
and
their
evaluation
will
grow
&
change
over
time
(similar
to
broader
impacts)
Peer
review
will
determine
next
steps
Community-‐driven
guidelines
– Different
disciplines
have
different
definitions
of
acceptable
data
sharing
– Flexibility
at
the
directorate
and
division
levels
– Tailor
implementation
of
DMP
requirement
Evaluation
will
vary
with
directorate,
division,
&
program
officer
*Unofficially
Help
from
Jennifer
Schopf,
NSF
19. DMPTool
Participants
CDL/UC3
Smithsonian
University
of
Illinois
• Trisha
Cruse
• Günter
Waibel
• Michael
Grady
• Perry
Willett
• Howard
Ding
• Marisa
Strong
UCLA
• Sarah
Shreeves
• Tracy
Seneca
• Todd
Grappone
• Scott
Fisher
• Gary
Thompson
University
of
Virginia
• Stephen
Abrams
• Sharon
Farbe
• Andrew
Sallans
• Mark
Reyes
• Darrow
Cole
• Sherry
Lake
• Margaret
Low
• Carla
Lee
• Carly
Strasser
UCSD
• Brad
Westbrook
Digital
Curation
Centre
DataONE
• Martin
Donnelly
• Amber
Budden
20. http://dmptool.org
Step-‐by-‐step
wizard
for
generating
DMP
Create
|
edit
|
re-‐use
|
share
|
save
|
generate
Open
to
community
Links
to
institutional
resources
Directorate
information
&
updates
21. Goals
of
the
DMPTool
I. Provide
researchers
a
simple
way
to
create
a
DMP
for
their
funding
agency
• Supply
questions
• Include
explanation/context
provided
by
the
agency
• Link
to
the
agency
website
for
policies,
help,
guidance
22. Goals
of
the
DMPTool
II. Provide
researchers
with
DMP
information
from
their
home
institution
• Resources
and
services
to
help
them
manage
data
• Help
text
for
specific
questions
• Suggested
answers
to
questions
• News
&
events
related
to
data
management
on
campus
23.
24.
25.
26.
27.
28.
29. Accessing
DMPTool
• DMPTool
added
to
campus
single
sign-‐on
service
(InCommon
/
Shibboleth)
• Researchers
use
their
campus
login
to
use
the
DMPTool
• Access
to
institution-‐specific
resources
30. Institution-‐Specific
Information
• Help
text
• Links
to
resources
and
services
• Suggested
answers
• Can
provide
specific
info
at
different
levels
– All
DMPs
– All
DMPs
for
a
particular
funding
agency
– A
question
within
a
data
management
plan
33. Increasing
Participation
Johns
Hopkins
University
UC
Merced
Organizations
Michigan
State
University
UC
Office
of
the
President
Moss
Landing
Marine
UC
San
Diego
with
Shibboleth
Laboratories
(CSU)
UC
San
Francisco
log-‐in
set
up
North
Carolina
State
University
of
Chicago
University
University
of
Illinois
at
American
University
Northwestern
University
Chicago
Arizona
State
University
Ohio
State
University
of
Illinois
at
Cal
Poly
State
University
Old
Dominion
University
Urbana-‐Champaign
Cal
State
Chico
Penn
State
University
of
Iowa
Cal
State
Fresno
Purdue
University
of
Miami
Cal
State
Los
Angeles
Rice
University
University
of
Michigan
Cal
State
Office
of
the
Smithsonian
Institution
University
of
Nebraska-‐
Chancellor
Texas
A&M
Lincoln
Clemson
University
Texas
State
University
San
University
of
North
Carolina-‐
George
Mason
University
Marcos
Chapel
Hill
Georgia
Tech
Tulane
University
University
of
Notre
Dame
Humboldt
State
University
University
of
Arizona
University
of
Texas
at
Austin
(CSU)
UC
Los
Angeles
University
of
Virginia
Indiana
University
UC
Berkeley
University
of
Wisconsin-‐
Iowa
State
University
UC
Davis
Madison
James
Madison
University
UC
Irvine
Yale
University
35. Assessment:
User
Survey
Did
you
use
these
features?
(n
=
62)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Links
to
Help
for
Suggested
DMP
News
DMPTool
Funder
Video
demo
resources
funder
answer
guide
requirements
question
Yes
No
36. Ongoing
Work
• Continually
updating
DMP
requirements
• Adding
funders:
NOAA,
Sloan,
NASA
• Adding
Functionality
for
editors
• Addressing
accessibility
issues
• Improving
speed
and
performance
• Articulating
security
&
privacy
policies
• Providing
multi-‐author
access
to
DMPs
(sharing)
37. Future
Work
• Integration
with
other
systems
and
initiatives
(e.g.,
Databib,
UNT?)
• Routing
DMPs
to
institutional
support
personnel
• Analytics
• Integrating
educational
materials
38. Governance
and
Sustainability
Self-‐funded
Sustainable
initiative
model
• Ideal
model:
Transparent
|
Nimble
|
Community
input
• Meeting
July
23-‐24
– Funded
by
DataONE
– Will
include
2
experts
to
facilitate
discussion
of
sustainability
and
governance
issues
– Cost
of
service
will
be
determined
prior
to
meeting
by
CDL
39. Final
Takeaways
1. Potential
to
be
a
data
management
focal
point
for
the
community
2. Can
function
as
the
coordinating
mechanism
for
an
institution
3. Can
be
used
to
scale
services
at
both
big
and
small
institutions,
with
or
without
dedicated
staff
40. How
UNT
Can
Participate
– Configure
Shibboleth
login
(“single
sign-‐on”)
– Add
links
to
local
resources,
help
text,
suggested
answers,
contact
information
– Blog
for
local
news
and
events
– Stay
tuned
for
updates
and
changes
after
July
governance
meeting
41. Questions?
• Contact
uc3:
uc3@ucop.edu
• Contact
me:
carly.strasser@ucop.edu
• Important
links:
– Info
on
Shibboleth
login:
https://dmp.cdlib.org/help/
dmp_shibboleth
– Funder
Templates:
https://bitbucket.org/dmptool/main/wiki/
Documentation
– DMPTool
Blog:
http://blogs.library.ucla.edu/dmptool