"Building communities and Services in Support of Data-Intensive Research". Webinar on 18 Sept 2013 for the NISO Webinar Series. This was part 2 of 2 for Data Curation

1. Building
Communities
&
Services
in
Support
of
Data-­‐Intensive
Research
From
Flickr
by
oennuja
NISO
webinar
17
Sept
2013
Carly
Strasser
|
California
Digital
Library
@carlystrasser

3. Why
is
data
curation
a
hot
topic?
From
Flickr
by
Velo
Steve

4. Back in the day…
Da
Vinci
Curie
Newton
classicalschool.blogspot.com
Darwin

5. Digital
data
From
Flickr
by
Flickmor
From
Flickr
by
US
Army
Environmental
Command
From
Flickr
by
DW0825
C.
Strasser
Courtesey
of
WHOI
From
Flickr
by
deltaMike

6. From
Flickr
by
~Minnea~
Data
management
Documentation
Reproducibility

7. From
Flickr
by
Michael
Tinkler

8. From
Flickr
by
Michael
Tinkler
Data
Curation

9. Data
curation
is
a
continuation
of
the
library’s
long-­‐standing
mission
to
connect
patrons
with
content
in
meaningful
ways
across
barriers
of
space
and
time.
-­‐
C
Tenopir
et
al.
2012
From
Flickr
by
neilio

10. From
Flickr
by
Richard
Eriksson
Culture
Shift
Ahead

11. Data
are
being
recognized
as
first
class
products
of
research
From
Flickr
by
Richard
Moross

12. Data
management
plans
Data
sharing
mandates
Data
publications
Data
citation
From
Flickr
by
torkildr

13. Plan
Collect
Describe
Analyze
Preserve
Share
Data
Life
Cycle

14. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
dmptool.org

15. Step-­‐by-­‐step
wizard,
open
to
community
Create,
edit,
re-­‐use,
share,
&
save
data
management
plans
Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share

17. Customization:
• Suggested
answers
• Help
text
• Resources

18. DMPTool
Uptake
0
100
200
300
400
500
600
700
800
0
1000
2000
3000
4000
5000
6000
NumberofInstitutions
NumberofPlans(solid)&UniqueUsers(dashed)
Unique Users
Plans
Institutions
736
5211
4519

19. DMPTool2:
Responding
to
the
Community
Administrator
interface
Open
API
/
Interoperability
Improved
functionality
Winter 2013-2014

20. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
dataup.cdlib.org

21. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
Open
source
tool
to
describe,
manage,
and
share
tabular
data

22. Features
Best
practices
check
Generate
metadata
Get
identifier
&
citation
Post
data
to
repository

24. • NSF
funding
via
DataONE
• Partnership
with
Microsoft
Research,
SDSC
• Enable
Customization
From
animationresources.org

25. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
merritt.cdlib.org

26. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
Repository
for
preservation
&
access
to
digital
assets

27. • Open
to
the
UC
community
and
external
partners
• Content-­‐agnostic
• Dark
archive
for
long-­‐term
preservation
• Bright
archive
for
sharing

28. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
was.cdlib.org

29. Analysis
tools
Full-­‐text
search
10,772
web
sites
Preserve
&
store
websites
“The
New
Internet”
from
siliconangle.com

30. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
n2t.net/ezid

31. Plan
>
Collect
>
Describe
>
Analyze
>
Preserve
>
Share
Create
persistent
identifiers
Manage
identifiers
&
associated
metadata
Resolve
identifiers

32. DOI:
10.1890/1540-­‐9295-­‐10.2.59
ARK:
90135/q13f4mjk
Resolver
Website
with
“object”

33.
ARKs
DOIs
IDF
EZID
CLIENTS
DOIs
DOIs
Where
are
these
identifiers
from?

34. EZID
CLIENTS

35. Identifiers
&
Data
Citation
Allows
readers
to
find
data
products
Get
credit
for
data
and
publications
Promotes
reproducibility
Better
measure
of
research
impact
Example:
Sidlauskas,
B.
2007.
Data
from:
Testing
for
unequal
rates
of
morphological
diversification
in
the
absence
of
a
detailed
phylogeny:
a
case
study
from
characiform
fishes.
Dryad
Digital
Repository.
doi:10.5061/dryad.20

36. Website
Email
Tweet
Slides
CDL
Blog
carlystrasser.net
carlystrasser@gmail.com
@carlystrasser
slideshare.net/carlystrasser
datapub.cdlib.org
cdlib.org/services/uc3