These are the Linked Data Applications slides that we presented at the Consuming Linked Data tutorial at WWW2010 in Raleigh, NC on April 26, 2010.
This slide set was not part of our tutorial that was presented at ISWC2009
2. What
is
a
Linked
Data
applica/on
• So@ware
system
that
makes
use
of
data
on
the
web
from
mul/ple
datasets
and
that
benefits
from
links
between
the
datasets
3. Characteris/cs
of
Linked
Data
Applica/ons
• Consume
data
that
is
published
on
the
web
following
the
Linked
Data
principles:
an
applica/on
should
be
able
to
request,
retrieve
and
process
the
accessed
data
• Discover
further
informa/on
by
following
the
links
between
different
data
sources:
the
fourth
principle
enables
this.
• Combine
the
consumed
linked
data
with
data
from
sources
(not
necessarily
Linked
Data)
• Expose
the
combined
data
back
to
the
web
following
the
Linked
Data
principles
• Offer
value
to
end-‐users
7. Linked
Data
and
E-‐Learning
• Netex
–
www.netex.es
• Enrich
their
e-‐learning
content
with
Dbpedia
and
Flickrwrapper
8. 1st
Linked
Data-‐a-‐thon
• Co-‐located
at
ISWC2009
• Spontaneous
and
organized
in
a
few
days
• Three
day
hacking
session
• Goal
was
to
develop
an
innova/ve
applica/on
that
showcase
the
virtues
of
Linked
Data.
• 8
par/cipa/ng
groups
9. Winners
• United
States
Linked
Data
Overlay
– Use
Linked
Data
about
geographical
loca/ons
and
display
it
on
Google
Earth.
• www.diversity-‐search.info
– Web
and
Image
search
engine
augmented
with
Linked
Data
– Pictures
of
David
Beckham
playing
football
in
the
different
clubs
he
has
played
for
• Find
tradi/onal
Chinese
medicine
as
an
alterna/ve
to
western
drugs
• iGoogr:
Imagine
Google
was
using
Good
Rela/ons
vocabulary
for
e-‐commerce
11. We
asked
ourselves…
• What
tools
were
used?
• What
datasets
were
used?
• How
was
auto
discovery
achieved?
• How
were
the
queries
wriSen?
• Which
vocabularies/ontologies
were
used?
• How
was
the
performance
of
the
applica/on?
• How
trustworthy
was
the
data?
12. Lessons
Learned
• Par/al
Unreliability
of
Infrastructure
– Querying
on-‐the-‐fly
– Overhead
of
transla/ng
HTTP
URIs
to
SPARQL,
then
to
SQL
and
then
back
• Lack
of
Interlinking
• Cross
dataset
querying
is
a
challenge
• Ignorance
to
licensing
and
informa/on
quality
• Discover
relevant
Linked
Data
is
an
open
problem