Learning from the Media: Encouraging Wonder and Discovery in Families and Sma...
DHWI Linked Open Data - Show and Tell
1. What
is
Linked
Open
Data?
#lod4h
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. What
is
it
good
for
(HUH!)?
#lod4h
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
Examples:
hPp://exhibi0ons.europeana.eu/,
hPp://pelagios-‐project.blogspot.com/
3. Modeling
and
Expressing
#lod4h
Using
established
and/or
custom
ontologies
Using
RDF
(Resource
Descrip0on
Framework)
RDF
Triples:
For
example:
A
URI
that
represents
the
person
Georgina
has
the
name
Georgina
Goodlander
<hPp://countedshadows.com/wordpress#>
foaf:hasName
“Georgina
Goodlander”
The
person
Georgina
in
this
URI
Is
the
same
thing
as
The
person
Georgina
in
this
URI
<hPp://countedshadows.com/wordpress#>
skos:exactMatch
<hPp://dbpedia.org/resource/Goodlander_G>
5. Steps
to
PublicaKon
#lod4h
Export
data
as
RDF
Publish
on
the
web
Celebrate!
hPp://linkeddatabook.com/edi0ons/1.0/#htoc61
6. Resources
&
Free
Stuff
to
Use!
#lod4h
Class
Syllabus
&
Wiki:
hPp://lod4h.pbworks.com
#lod4h
Open
Refine
for
cleaning
data
and
assigning
RDF
proper0es:
hPps://github.com/OpenRefine
Protégé
for
crea0ng
and
edi0ng
ontologies:
hPps://github.com/OpenRefine
Data
Hub
for
finding
other
open
data
sets:
hPp://datahub.io/
Challenges?
Few
exis0ng
examples
of
applica0on
Limita0ons
of
established
ontologies
Conceptualizing
messy
data
is
hard
Daun0ng
scale
Developing
and
maintaining
automa0on
and
workflow
Time
and
resources