Overview of the project at the Smithsonian American Art Museum to publish its collections data as 5-star Linked Open Data.

1. Linking
the
American
Art
Museum
to
the
Cloud
What
is
Linked
Open
Data?
Data
published
by
exis0ng
internet
protocols
that
use
a
URI
(Unique
Resource
Indicator)
as
the
primary
discoverable
en0ty
for
a
resource
(e.g.
person,
object,
web
page,
etc.)
THE
FIVE
STARS
OF
LOD:
★
make
your
stuff
available
on
the
web
(whatever
format)
under
an
open
license
★★
make
it
available
as
structured
data
(e.g.,
Excel
instead
of
image
scan
of
a
table)
★★★
use
non-­‐proprietary
formats
(e.g.,
CSV
instead
of
Excel)
★★★★
use
URIs
to
iden0fy
things,
so
that
people
can
point
at
your
stuff
★★★★★
link
your
data
to
other
data
to
provide
context

2. Linking
the
American
Art
Museum
to
the
Cloud
What
is
good
for?
• Making
your
data
more
discoverable
and
useful
by
everybody
• Making
the
web
machine-­‐readable
at
a
more
granular
level
• Allowing
for
more
sophis0cated
queries
using
inference
• Connec0ng
your
data
to
other
people’s
data
For
American
Art,
Linked
Open
Data
will:
• Make
our
collec0ons
data
more
findable
on
the
web
• Create
connec0ons
with
other
museums
that
have
related
artworks
• Create
connec0ons
with
other
non-­‐museum
resources,
such
as
the
New
York
Times
• Create
connec0ons
with
our
dispersed
content
on
social
media
(e.g.
Flickr)
• Help
us
beSer
adapt
to
the
changing
web

3. Linking
the
American
Art
Museum
to
the
Cloud
Examples
Europeana
• Digi0zed
collec0ons
of
museums,
libraries,
archives
and
galleries
across
Europe.
• Open
metadata
on
20
million
texts,
images,
videos
and
sounds
• A
subset
of
2.4
millions
objects
from
8
direct
Europeana
providers
encompassing
over
200
cultural
ins0tu0ons
from
15
countries
is
served
according
to
the
Linked
Data
recipes.
• Virtual
exhibi0ons
showcase
some
of
the
content
available.

4. Linking
the
American
Art
Museum
to
the
Cloud
Examples
Pelagios
• Stands
for
'Pelagios:
Enable
Linked
Ancient
Geodata
In
Open
Systems’
• Aim
is
to
help
introduce
Linked
Open
Data
into
online
resources
that
refer
to
places
in
the
Ancient
World.
• Allows
you
to
find
content
related
to
a
specific
place

5. Linking
the
American
Art
Museum
to
the
Cloud
GeJng
Started
IniKal
QuesKons
• Will
it
take
a
lot
of
0me
and
resources
to
prepare
our
data?
• How
does
LOD
differ
from
what
a
Google
search
can
do?
• Is
it
foolish
to
be
doing
this
before
standards
are
in
place?
• What
if
people
create
inappropriate
links
to
our
data?
• Will
it
be
worth
the
0me
and
effort
in
the
end?
• How
do
we
handle
all
of
the
non-­‐public
data
that
we
have?
• Is
it
possible
to
make
sense
of
all
the
acronyms?
The
Project
• Working
with
the
Informa0on
Sciences
Ins0tute
(ISI)
and
Department
of
Computer
Science
at
the
University
of
Southern
California.
• Goal:
Publish
5-­‐star
Linked
Open
Data
of
our
complete
collec0ons
data
(41,000
objects,
8,000
ar0sts).
• Project
Phases:
Prepare
the
data,
Create
an
ontology,
map
the
data
to
RDF,
link
the
data
to
hub
datasets,
publish
the
data.

6. Linking
the
American
Art
Museum
to
the
Cloud
The
Process
Preparing
the
data
• Collec0ons
data
is
stored
in
TMS.
We
have
over
100
tables
• We
decided
to
publish
only
the
data
that
is
already
visible
on
our
website
• We
used
an
exis0ng
output
report
from
our
database
• Several
fields
needed
to
be
interpreted
first
before
they
could
be
mapped
to
RDF
Designing
the
Ontology
• We
built
our
ontology
around
exis0ng
ontologies
• An
augmented
version
of
Europeana
Data
Model
v.2
for
overall
framework;
SKOS
for
classifica0on
of
artworks,
ar0st
and
place
names;
Dublin
Core
for
tombstone
data;
RDA
Group
2
Elements
for
biographical
informa0on;
schema.org
for
geographical
data.

7. Linking
the
American
Art
Museum
to
the
Cloud
The
American
Art
Ontology

8. Linking
the
American
Art
Museum
to
the
Cloud
The
Process
Mapping
the
Data
to
RDF
(Resource
DescripKon
Framework)
• Used
KARMA
tool
to
model
the
data
• The
system
learns
with
each
dataset
so
the
process
becomes
easier
and
faster
For
Example:
Subject
Predicate
Object
www.americanart.si.edu/linkeddata/person/3406
saam:Person
“Thomas
Moran”
www.americanart.si.edu/linkeddata/person/3406
rdaGr2:dateOfBirth
“1837”
www.americanart.si.edu/linkeddata/person/3406
owl:SameAs
hSp://live.dbpedia.org/page/Thomas_Moran

9. Linking
the
American
Art
Museum
to
the
Cloud
The
Process
Linking
the
Data
to
External
Data
• Verify
matches
before
publishing
• Have
already
linked
ar0sts
to:
• DBPedia
-­‐
2,194
• New
York
Times
-­‐
70
• Addi0onally,
can
link
ar0sts
to:
• GeSy
Union
List
of
Ar0st
Names
-­‐
2,110
(ULAN
is
not
yet
published
as
LOD,
but
will
be)
• Rijksmuseum
dataset
–
551
(links
are
not
yet
verified)
• In
the
works:
• Linking
places
to
GeoNames
• Linking
concepts
to
AAT
• Linking
to
datasets
from
other
museums
• Linking
to
social
media
content
Publishing
• Plan
to
publish
complete
dataset
and
all
verified
links
under
a
CC0
license
• Data
will
be
CC0,
but
images
will
be
maintained
under
a
restricted
license
• Include
example
records
and
SPARQL
endpoint

10. Linking
the
American
Art
Museum
to
the
Cloud
Some
answers
Answers
to
IniKal
QuesKons:
• Will
it
take
a
lot
of
0me
and
resources
to
prepare
our
data?
• Using
KARMA
to
model
the
data
and
a
visual
interface
to
verify
the
links
reduced
the
staff
Eme
that
would
have
been
needed
to
do
this
manually.
Working
with
ISI
certainly
helped
kick-­‐start
the
process.
• How
does
LOD
differ
from
what
a
Google
search
can
do?
• LOD
eliminates
the
“noise”
of
a
Google
search.
With
LOD
you
can
query
specific
facts.
With
Google
you
query
documents
and
then
have
to
read
the
document
to
get
the
facts.
• Is
it
foolish
to
be
doing
this
before
standards
are
in
place?
• There
are
already
some
standards
in
place.
Plus,
being
one
of
the
first
means
that
we
have
the
opportunity
to
help
shape
the
standards.
• What
if
people
create
inappropriate
links
to
our
data?
• You
cannot
control
what
people
say
about
you
on
the
internet!
• Will
it
be
worth
the
0me
and
effort
in
the
end?
• We
believe
so!
It
will
allow
us
to
beTer
adapt
to
the
future
of
the
web.
• How
do
we
handle
all
of
the
non-­‐public
data
that
we
have?
• We
opted
to
publish
only
our
public
data.
• Is
it
possible
to
make
sense
of
all
the
acronyms?
• Yes!
It
takes
Eme,
but
you
do
eventually
grasp
all
the
different
terms.

11. Linking
the
American
Art
Museum
to
the
Cloud
Some
conclusions
• We
ini0ally
planned
to
use
only
a
sample
of
collec0ons
data.
In
the
end,
we
used
data
for
our
en0re
collec0on
–
over
41,000
objects!
• Linking
to
datasets
like
DBPedia
and
the
New
York
Times
will
greatly
expand
the
content
we
offer
on
our
website.
• Linking
to
datasets
from
other
art
museums
will
increase
the
accessibility
and
reach
of
art
collec0ons
and
cultural
heritage
online.
• We’re
excited
for
the
poten0al
to
link
to
our
content
on
social
media
sites
–
an
object
page
as
a
“hub”
to
all
types
of
content
about
that
object.
• We
see
great
poten0al
in
using
Linked
Open
Data
to
curate
stories
about
artworks
and
ar0sts
that
connect
museums
and
datasets
around
the
world
in
new
and
surprising
ways.

12. Linking
the
American
Art
Museum
to
the
Cloud
What’s
next?
• Embedding
linked
content
on
object
pages
and
ar0st
pages
on
our
website
(Wikipedia,
the
New
York
Times,
etc.)
• Improve
representa0on
of
ar0sts
on
Wikipedia,
adding
ar0cles
and
infoboxes
where
possible
to
increase
the
number
of
matches
in
DBPedia.
• Create
an
ongoing
maintenance
plan
to
ensure
that
the
linked
open
data
reflect
new
and
edited
museum
data.
• Tag
object-­‐
and
person-­‐related
museum
content
on
social
sites
like
Flickr
and
YouTube
so
that
we
can
create
links
to
that
content
on
our
website,
too.
• Inves0gate
mapping
and
linking
an
artwork’s
subject.
• Expand
the
LOD
in
ways
that
will
enhance
research.
• Create
a
tool
that
allows
users
to
“curate
stories”
using
LOD:
• hSp://prezi.com/htrvh2jrcsio/cura0ng-­‐stories-­‐with-­‐linked-­‐open-­‐data/
• Encourage
others
to
build
applica0ons
with
our
data.