Cal Poly - Data Management and the DMPTool

From
Flickr
by
OZinOH

The
Data
Management

Planning
Tool

DMPTool

Carly
Strasser

|
@carlystrasser

California
Digital
Library

Cal
Poly

Oct
2013

Roadmap

Background

Current
DMP
tools

A
walkthrough
of

DMPTool

From
Flickr
by

(Luciano)

DMPTool2

From
Flickr
by
US
Army
Environmental
Command

From
Flickr
by

deltaMike

From
Flickr
by

DW0825

C.
Strasser

From
Flickr
by
Flickmor

Courtesey
of
WHOI

Data
management

Documentation

Reproducibility

From
Flickr
by
~Minnea~

From
Flickr
by

ahockey

DMP
s!

What
is
a
data

management
plan?

A
document
that
describes

what
you
will
do
with
your

data
both

during
your
research

and
after
you
complete

your
project

From
Flickr
by
Barbies
Land

From
Flickr
by
401(K)
2013

For
funders:

A
short
plan
submitted

alongside
grant
applications

An
outline
of

– 
– 
– 
– 
– 
– 

what
will
be
collected

methods

But
they

Standards
all
have

diﬀerent
requirements

Metadata

and
express
them
in

sharing/access

diﬀerent
ways

long-‐term
storage

Includes
how
and
why

Why
prepare
a
DMP?

From
Flickr
by
natalinha

•  Saves
time

•  Increases
research

eﬃciency

•  Satisﬁes
requirements

When
do
you
plan?

Yes.

When
do
you
plan?

Plan

Proposal

writing

Research

Ideas

Collect

Analyze

Assure

Integrate

Discover

Publication

Describe

Preserve

Remember!

From
Flickr
by
gmacfadyen

•  Keep
your
plan
current

•  Incorporate
changes

•  Use
as
a
guide
for
daily

activities

Where
to
start?

From
Flickr
by
celikins

Small
&
Simple

•  Document
what
you
know
now

•  Share
the
plan
with
your
team

•  Avoid
procrastination
and
immobilization

Where
to
start?

Courtesy
of
Martin
Donnelly

Research
Support

Oﬃce

Data
Library
/
Repository

Researcher

DMP?

Unruly

Data

Computing

Support

Faculty
Ethics

Committee

Etc...

Who:
Support
Services
&

Collaborators

Plan
section

Support

Information
about
data

PI,
co-‐PIs,
research
staff

Metadata
content
&
format

Librarians,
data
repositories

Policies
for
access,
sharing,

reuse

Funder,
institute,
HIPPA,
IRB,

users

Long-‐term
storage
and
data

management

Librarians,
IT
staff,
data

repositories

Budget

Sponsored
programs
office,

funder

DMPs:
A
Short
History

Liz
Lyon:
Dealing

with
Data

2008

UK
funder
expectations

2009

2009-‐10

DMPs:
A
Short
History

Across
the
Pond…

Federal
Funding
Accountability

and
Transparency
Act

2006

2010
–
present

2010

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

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

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?

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?

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

Don’t
forget:
Budget

•  Costs
of
data
preparation
&
documentation

Hardware,
software

Personnel

Archive
fees

•  How
costs
will
be
paid

Request
funding!

dorrvs.com

*

NSF’s
Vision

DMPs
and
their
evaluation
will
grow
&

change
over
time

Peer
review
will
determine
next
steps

Community-‐driven
guidelines

Evaluation
will
vary
with
directorate,

division,
&
program
oﬃcer

*Unoﬃcially

A
DMP
Example
(1)

• 
• 

Project
name:
Effects
of
temperature
and
salinity
on
population
growth
of
the
estuarine

copepod,
Eurytemora
affinis

Project
participants
and
affiliations:

Carly
Strasser
(University
of
Alberta
and
Dalhousie
University)

Mark
Lewis
(University
of
Alberta)

Claudio
DiBacco
(Dalhousie
University
and
Bedford
Institute
of

Oceanography)

•  Funding
agency:
CAISN
(Canadian
Aquatic
Invasive
Species
Network)

• 

•  Description
of
project
aims
and
purpose:

• 
We
will
rear
populations
of
E.
affinis
in
the
laboratory
at
three
temperatures
and
three

salinities
(9
treatments
total).
We
will
document
the
population
from
hatching
to
death,

noting
the
proportion
of
individuals
in
each
stage
over
time.
The
data
collected
will
be
used

to
parameterize
population
models
of
E.
affinis.
We
will
build
a
model
of
population
growth

as
a
function
of
temperature
and
salinity.
This
will
be
useful
for
studies
of
invasive
copepod

populations
in
the
Northeast
Pacific.

•  Video
Source:
Plankton
Copepods.
Video.

Encyclopædia
Britannica
Online.

Web.
13
Jun.
2011

A
DMP
Example
(2)

• 
• 

• 

1.
Information
about
data

Every
two
days,
we
will
subsample
E.
affinis
populations
growing
at
our

treatment
conditions.

We
will
use
a
microscope
to
identify
the
stage
and

sex
of
the
subsampled
individuals.

We
will
document
the
information
first

in
a
laboratory
notebook,
then
copy
the
data
into
an
Excel
spreadsheet.
For

quality
control,
values
will
be
entered
separately
by
two
different
people
to

ensure
accuracy.

The
Excel
spreadsheet
will
be
saved
as
a
comma-‐
separated
value
(.csv)
file
daily
and
backed
up
to
a
server.
After
all
data
are

collected,
the
Excel
spreadsheet
will
be
saved
as
a
.csv
file
and
imported

into
the
program
R
for
statistical
analysis.
Strasser
will
be
responsible
for
all

data
management
during
and
after
data
collection.

Our
short-‐term
data
storage
plan,
which
will
be
used
during
the

experiment,
will
be
to
save
copies
of
1)
the
.txt
metadata
file
and
2)
the

Excel
spreadsheet
as
.csv
files
to
an
external
drive,
and
to
take
the
external

drive
off
site
nightly.

We
will
use
the
Subversion
version
control
system
to

update
our
data
and
metadata
files
daily
on
the
University
of
Alberta

Mathematics
Department
server.
We
will
also
have
the
laboratory
notebook

as
a
hard
copy
backup.

A
DMP
Example
(3)

•  2.

Metadata
format
&
content

• 
We
will
first
document
our
metadata
by
taking
careful
notes
in
the
laboratory

notebook
that
refer
to
specific
data
files
and
describe
all
columns,
units,

abbreviations,
and
missing
value
identifiers.

These
notes
will
be
transcribed
into

a
.txt
document
that
will
be
stored
with
the
data
file.

After
all
of
the
data
are

collected,
we
will
then
use
EML
(Ecological
Metadata
Language)
to
digitize
our

metadata.
EML
is
on
of
the
accepted
formats
used
in
Ecology,
and
works
well
for
the

type
of
data
we
will
be
producing.
We
will
create
these
metadata
using
Morpho

software,
available
through
the
Knowledge
Network
for
Biocomplexity
(KNB).
The

documentation
and
metadata
will
describe
the
data
files
and
the
context
of
the

measurements.

A
DMP
Example
(4)

3.

Policies
for
access,
sharing
&
reuse

• 
We
are
required
to
share
our
data
with
the
CAISN
network
after
all
data

have
been
collected
and
metadata
have
been
generated.
This
should
be
no

more
than
6
months
after
the
experiments
are
completed.

In
order
to
gain

access
to
CAISN
data,
interested
parties
must
contact
the
CAISN
data

manager
(data@caisn.ca)
or
the
authors
and
explain
their
intended
use.

Data
requests
will
be
approved
by
the
authors
after
review
of
the
proposed

use.

• 
The
authors
will
retain
rights
to
the
data
until
the
resulting
publication
is

produced,
within
two
years
of
data
production.

After
publication
(or
after

two
years,
whichever
is
ﬁrst),
the
authors
will
open
data
to
public
use.

After

publication,
we
will
submit
our
data
to
the
KNB
allowing
discovery
and
use

by
the
wider
scientiﬁc
community.
Interested
parties
will
be
able
to

download
the
data
directly
from
KNB
without
contacting
the
authors,
but

will
still
be
encouraged
to
give
credit
to
the
authors
for
the
data
used
by

citing
a
KNB
accession
number
either
in
the
publication’s
text
or
in
the

references
list.

A
DMP
Example
(5)

4.

Long-‐term
storage
and
data
management

The
data
set
will
be
submitted
to
KNB
for
long-‐term
preservation
and

storage.

The
authors
will
submit
metadata
in
EML
format
along
with

the
data
to
facilitate
its
reuse.
Strasser
will
be
responsible
for

updating
metadata
and
data
author
contact
information
in
the
KNB.

•  5.

Budget

• 
A
tablet
computer
will
be
used
for
data
collection
in
the
ﬁeld,
which

will
cost
approximately
$500.

Data
documentation
and
preparation

for
reuse
and
storage
will
require
approximately
one
month
of
salary

for
one
technician.
The
technician
will
be
responsible
for
data
entry,

quality
control
and
assurance,
and
metadata
generation.
These
costs

are
included
in
the
budget
in
lines
12-‐16.

From
Flickr
by
thewmatt

From
Flickr
by
Max
Chu

dmptool.org

DMPTool
Project

•  Partners
started
working
in
January
2011

•  Developed
requirements,
divided
work

•  Self-‐funded
/
In-‐kind

dmptool.org

•  Free

•  Guides
through
creating
a
DMP

•  Helps
meet
funder
requirements

•  Supplies
questions

•  Includes
explanation/context
provided
by

the
agency

•  Provides
links
to
the
agency
website

Wait!

Data
management
planning

is
complex
&
requires
dialog

Range
of
support
&

understanding

Our
focus:

•  simplify
&
scale
the
common
parts

•  develop
community

•  provide
incremental
improvement

in
functionality

From
Flickr
by
ChrisGoldNY

Access

DMPTool
can
be
added
to

campus
single
sign-‐on

service

Researchers
use
campus

login
to
access
tool

From
Flickr
by
Clonny

Researchers

like
it
here

Institution-‐speciﬁc…

•  Help
text

•  Links
to
resources
&
services

•  Suggested
answers

…at
diﬀerent
levels

•  All
DMPs

•  All
DMPs
for
a
particular

funding
agency

•  Question
within
a
data

management
plan

Customized

Resources

From
Flickr
by
lumachrome

From
Flickr
by
OZinOH

DMPTool2

DMPTool
Uptake

1000

900

6000

800

5000

700

600

4000

500

3000

400

300

2000

1000

0

Unique
Users

Plans

Institutions

200

100

0

Number
of
Institutions

Number
of
Plans
(solid)
&
Unique
Users
(dashed)

7000

DMPTool
2:

Responding
to
the
Community

ming

Co
oon!

S

2
Plan

Creators

&

Plan

Administrators

2
Improvements
for
Plan
Creators

•  Collaborative
plan
creation

•  Role-‐based
user
authorization
&
access

•  Better
plan
templates
&
resources

2
New
administrator
Interface

•  Template
creation:

•  Better
plan
template
granularity

discipline,
funder,
question

What
tgranularity

•  Better
institution
his
means
for
plan

creators:

department,
college,
lab
group,
…

•  Better
plans

•  Enhanced
search
and
browse
of
plans

•  Access
to
m•  More
granular
help

etrics
for
reporting
&
follow-‐up

•  Local
input
&
assistance

2

Open
RESTful
API

?

Yelp

APIs

Google
Maps

DMPTool

API

Other
stuﬀ

•  Carefully
thought
out
code

•  Invisible
to
user

•  Expose
speciﬁc
functionality

and/or
data

•  Other
functionality/data

protected

API
Beneﬁts

Interactions

Improve
functionality

Add
more
functionality

Combine
with
their
services

Popularity

IMLS
Grant

Improving
Data

Stewardship
with
the

DMPTool

Provide
librarians
with
the

tools
and
resources

to
claim
the
data
management
education
space

Questions?

Website

Twitter

Blog

dmptool.org

@TheDMPTool

blog.dmptool.org

Email

Tweet
me

My
slides

carly.strasser@ucop.edu

@carlystrasser

slideshare.net/carlystrasser

Cal Poly - Data Management and the DMPTool

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