This presentation was provided by Karen Baker, University of Illinois - Urbana-Champaign, during a NISO Virtual Conference on the topic of data curation, held on Wednesday, August 31, 2016

1.
A
Mul&-­‐Decade
Case:
The
Evolu&on
of
Data
Products
and
Designated
Audiences
NISO
2016
Karen
S.
Baker
Graduate
School
of
Informa<on
Sciences
University
of
Illinois
Urbana-­‐Champaign
1

2. The
story
traces
the
evolu<on
of
a
set
of
data
products,
asking
• How
is
knowledge
mobilized?
• What
are
the
data
products?
• Who
are
the
designated
communi<es?
We
present
a
three
decade
data
story
• Karen
Baker,
Ruth
Duerr,
and
Mark
Parsons,
• Scien<fic
Knowledge
Mobiliza<on:
Co-­‐evolu<on
of
Data
Products
and
Designated
Communi<es
• Interna<onal
Journal
of
Digital
Cura<on
10(2),
2015
A
Story
About
Data
Product
Development
Note
on
coauthors:
Ruth
Duerr
now
at
Ronin
Ins<tute
for
Independent
Scholarship
Mark
Parsons
now
Secretary
General
of
the
Research
Data
Alliance
(RDA)
2

3. Where
the
Story
Takes
Place:
Na<onal
Snow
and
Ice
Data
Center
(NSIDC):
From
Baker
&
Duerr,
in
press,
Data
&
the
Diversity
of
Repositories.
In
Cura<ng
Research
Data:
A
Handbook
of
Current
Prac<ce
NSIDC
NSIDC
3

4. A
data
product
is
data
at
a
par<cular
stage
of
processing
that
can
be
iden<fied
uniquely
and
described.
Digital
Data
Products
Kinds
of
data
products
• Ini<al
recorded
data
• Calibrated
data
• Cleaned
data
• Gridded/Interpolated
data
• Interpreted
data
• Derived
data
• Transformed
data
• Synthesized
data
Note:
Data
product
development
is
influenced
by
the
intended
use
of
the
product.
4

5. Discussion
Points
• Data
Product
Descrip<on
§ Collec<on
of
data
products
§ Data
product
teams
• Data
Product
Development
§ Mul<-­‐level
collec<on
§ Mul<-­‐cycle
trajectory
• Data
Product
Delivery
§ Diverse
audiences
§ Mul<-­‐mode
communica<on
5

6. Collec<on
of
Sea
Ice
Data
Products
Redrawn
circa
2010
from
original
work
by
Donna
Scoa,
who
manages
the
NSIDC
Passive
Microwave
Product
Team.
Preliminary
–
gold
box
Source
–
brown
box
Final
–
green
hexagon
Near
real-­‐<me
–
blue
oval
Value
added
–
red
octagon
6

7. NSIDC-­‐0081
Near-­‐Real-­‐Time
DMSP
SSM/I
Daily
Polar
Gridded
Sea
Ice
Concentra<ons
Remote
Sensing
Systems
F17
Tbs
(Wentz)
NSIDC-­‐001
SSM/I
Polar
Gridded
Tbs
NSIDC-­‐0051
Preliminary
Sea
Ice
Concentra<ons
from
Nimbus-­‐7
SSMR
and
DMSP
SSM/I
NSIDC-­‐0051
Sea
Ice
Concentra<ons
from
Nimbus-­‐7
SSMR
and
DMSP
SSM/I
G02135
Sea
Ice
index
Arc<c
Sea
Ice
News
and
Analysis
From
the
Sea
Ice
Data
Products
Collec<on
Preliminary
–
gold
box
Source
–
brown
box
Final
–
green
hexagon
Near
real-­‐<me
–
blue
oval
Value
added
–
red
octagon

8. Data
Product
Teams
Roles
-­‐
Skill
Sets
• Data
managers
• Programmers
• Technical
writers
• Scien<sts
• Instrument
engineers
• Science
communicators
• Systems/Database
managers
• User
support
specialists
8

9. Data
Product
Team
Intermediaries
Roles
-­‐
Skill
Sets
• Data
managers
• Programmers
• Technical
writers
• Scien<sts
• Instrument
engineers
• Science
communicators
• Systems/Database
managers
• User
support
specialists
“This
ac<ve
human
element
of
data
management
is
not
always
recognized
by
funding
agencies,
nor
is
it
explicit
in
the
OAIS
Reference
Model
…”
–
Parsons
and
Duerr,
2005
Parsons,
M.
A.,
&
Duerr,
R.
(2005).
Designa<ng
user
communi<es
for
scien<fic
data:
challenges
and
solu<ons.
Data
Science
Journal,
4,
31-­‐38.
Intermediaries
9

10. OAIS
Reference
Model
A
Narra<ve
Framework:
Open
Archive
Informa<on
System
OAIS Archive
Ingest
Access
Archive
Data
Mgmt
Administration
Producer
Preservation Planning
Consumer
MANAGEMENT
SIP
AIP AIP
DIP
Descriptive
Information
Descriptive
Information
Func4onal
model
CCSDS.
(2012).
Consulta<ve
Commiaee
for
Space
Data
Systems,
Reference
Model
for
an
Open
Archival
Informa<on
System
(OAIS).
Washington
DC:
CCSDS
650.0-­‐M-­‐2,
Magenta
Book.
Issue
2.
June
2012.
10

11. OAIS
Reference
Model
Informa4on
Package
Concepts
CCSDS.
(2012).
Consulta<ve
Commiaee
for
Space
Data
Systems,
Reference
Model
for
an
Open
Archival
Informa<on
System
(OAIS).
Washington
DC:
CCSDS
650.0-­‐M-­‐2,
Magenta
Book.
Issue
2.
June
2012.
Submission
Informa<on
Package
Preserva<on
Informa<on
Package
Dissemina<on
Informa<on
Package
SIP
PIP
DIP
11

12. OAIS
Reference
Model
OAIS
Archive
Responsibili4es
CCSDS.
(2012).
Consulta<ve
Commiaee
for
Space
Data
Systems,
Reference
Model
for
an
Open
Archival
Informa<on
System
(OAIS).
Washington
DC:
CCSDS
650.0-­‐M-­‐2,
Magenta
Book.
Issue
2.
June
2012.
•
Nego<ate
for
and
accept
informa<on
•
Obtain
sufficient
control
to
ensure
long-­‐term
preserva<on
•
Designate
one
or
more
communi<es
as
designated
audience
who
should
be
able
to
understand
what
is
•
Ensure
that
the
informa<on
is
independently
understandable
to
them
•
Follow
documented
procedures
and
policies
for
data
preserva<on
and
access
•
Make
the
informa<on
available
with
evidence
suppor<ng
its
authen<city
haps://public.ccsds.org
12

13. The
Data
Landscape:
In
Development
Data
System
Informa<on
System
Data
Repository
Data
Archive
Dataset
Data
set
Data
Package
Metadata
repositories
web
of
Data
Data
Element
&
Interconnec<ons
13

14. Discussion
Points
• Data
Product
Descrip<on
ü Collec<on
of
data
products
ü Data
product
teams
• Data
Product
Development
§ Mul<-­‐level
collec<on
§ Mul<-­‐cycle
trajectory
• Data
Product
Delivery
§ Diverse
audiences
§ Mul<-­‐mode
communica<on
14

15. Sea
Ice
Data
Products:
Dependencies
&
Levels
15

16. Levels
of
Data
Products
16

17. Con<nuing
Development
of
Data
Products
17

18. Figure
2.
A
simplified
view
of
the
con<nuing
development
of
scien<fic
data
products.
Each
cycle
is
ini<ated
by
one
or
more
events
that
create
a
new
audience
that
leads
to
genera<on
of
a
new
data
product
in
response
to
the
needs
of
a
recently
iden<fied
designated
user
community.
Data
Products:
Mul<-­‐cycle
Trajectory
18

19. Discussion
Points
• Data
Product
Descrip<on
ü Collec<on
of
data
products
ü Data
product
teams
• Data
Product
Development
ü Mul<-­‐level
collec<on
ü Mul<-­‐cycle
trajectory
• Data
Product
Delivery
§ Diverse
audiences
§ Mul<-­‐mode
communica<on
19

20. To
a
remote
sensing
community,
the
world
is:
• Large-­‐scale
earth
coverage
using
well-­‐defined
plaoorms
• A
series
of
images
with
gridded
pixels
that
can
be
manipulated
computa<onally
To
ecologists,
the
world
is:
• A
set
of
observa<ons/measurements
captured
as
parameters
such
as
temperature
and
popula<on
counts
• A
system
of
interac<ng
systems
with
dependencies
among
the
parameters
that
vary
con<nuously
To
the
public,
the
world
is:
• The
place
within
which
their
neighborhood
resides
• A
place
where
decision-­‐making
is
increasing
in
complexity
due
to
the
interdependencies
of
natural
systems
and
human
systems
*
following
Mark
Parsons,
Ben
Domenico,
and
Stefano
Na<vi
Who
is
the
audience?
What
is
their
worldview?
20

21. Greenland
Ice
Sheet
Melt
Data
Products
21

22. Knowledge
Mobilized
via
Data
Product
Genera<on
1.
Data
workforce
and
data
work
are
changing
• Data
product
descrip<on
ü Collec<on
of
data
products
ü Data
product
teams
2.
Data
products
gain
value
curated
as
a
con<nuing
collec<on
• Data
product
development
ü Mul<-­‐level
collec<on
ü Mul<-­‐cycle
trajectory
3.
Data
product
delivery
takes
many
forms
• Data
product
delivery
ü Diverse
audiences
ü Mul<-­‐mode
communica<on
22

23. Developing
the
Workforce
for
Data
NRC
(2015).
Preparing
the
Workforce
for
Digital
Cura<on:
Commiaee
on
Future
Career
Opportuni<es
and
Educa<onal
Requirements
for
Digital
Cura<on;
Board
on
Research
Data
and
Informa<on;
Policy
and
Global
Affairs.
23

24. Developing
Workforce
for
Data
Work
Making the time to tell the story
… to multiple audiences
… in multiple formats
… with multiple intermediaries
24

25. Karen
Baker
karensbaker@gmail.com
25

26. Karen
Baker
karensbaker@gmail.com
Acknowledgement:
Data
Cura<on
Educa<on
in
Research
Centers
(DCERC)
project,
funded
by
the
Ins<tute
of
Museum
and
Library
Services
(RE-­‐02-­‐10-­‐0004-­‐10),
co-­‐led
by
Carole
Palmer.
Par<cipants
at
the
Na<onal
Snow
and
Ice
Data
Center
including
Donna
Scoa
who
manages
the
NSIDC
Passive
Microwave
Product
Team.
26