The document discusses Triple Pattern Fragments (TPF), which is an alternative approach to publishing Linked Data compared to SPARQL endpoints and data dumps. TPF servers are simpler and have lower processing costs than SPARQL endpoints. This allows TPF interfaces to have very high availability for clients. The document analyzes usage statistics of the DBpedia TPF interface which show it has been widely used with high uptime. It advocates for TPF as a way to make it easier and more realistic to build applications on live Linked Data.

1. DBpedia's
Triple Pattern Fragments
Ruben Verborgh

2. Building applications with
Linked Data from the Web
should become as realistic
and easy as using Web APIs.

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Tomasz
Pluskiewicz @tpluscode · Jan 28
LinkedDataFragments retweeted
I finally really understood @LDFragments
videolectures.net/iswc2014_verbo… via @videolectures
2 2
Miel
Vander
Sande @Miel_vds · Jan 23
LinkedDataFragments retweeted
There’s a @LDFragments #Java client bit.ly/1yWVCWW & server
bit.ly/1AXPpVK. Under develop, help welcome! #semweb #LinkedData
View summary2 4
Ruben
Verborgh @RubenVerborgh · Jan 22
LinkedDataFragments retweeted
My #ISWC2014 talk “Querying datasets on the Web with high
availability”: explains #RDF #API trade-offs.
videolectures.net/iswc2014_verbo… @LDFragments
3 9
Ruben
Verborgh @RubenVerborgh · Jan 12
LinkedDataFragments retweeted
“The @LDFragments server design lets us publish and query @OrgRef
data using a free Heroku instance.”
—@tedlawless lawlesst.github.io/notebook/orgre…
1 2
Ted
Lawless @tedlawless · Jan 11
LinkedDataFragments retweeted
Notebook: mapping @OrgRef to RDF and publishing with @LDFragments.
Next up matching to @VIVOcollab instances.
lawlesst.github.io/notebook/orgre…
9 11
LinkedDataFragments @LDFragments · Dec 17
First Triple Pattern Fragments server running on Heroku, set up by
@tedlawless. github.com/LinkedDataFrag… #affordable #LinkedData
View summary1 2
LinkedDataFragments @LDFragments · Nov 26
Querying Linked Data in HTML5 has never been easier: via a simple tag,
you can query in a streaming or polling way github.com/tomayac/polyme
…
View summary5 9

4. The easy part is covered.
All triples look the same:
subject – predicate – object.
That’s a major advantage
over 15.000+ different APIs.

5. But is it also realistic?
<95%
MORE THAN HALF
of public SPARQL endpoints
AVAILABILITY
Buil-Aranda – Hogan – Umbrich – Vandenbussche
SPARQL Web-Querying Infrastructure: Ready for Action?

6. We design simpler server interfaces
to publish Linked Data at low cost,
making clients solve complex queries.
We host a DBpedia interface,
and hope to inspire you to
build cool DBpedia applications.

7. About DBpedia’s fragments
Usage analysis so far
Fragments in the future

8. About DBpedia’s fragments
Usage analysis so far
Fragments in the future

9. Classic Linked Data publishing:
simple client, hard-working server.
client server
SELECT * WHERE {
?person a dbpedia-owl:Writer;
rdfs:label ?name;
dbpedia-owl:almaMater[ rdfs:label "Trinity College, Dublin"@en ].
FILTER LANGMATCHES(LANG(?name), "EN")
}

10. SPARQL endpoints have to work hard
in comparison to other servers.
server
highly individualized requests
low cacheability
large per-request processing cost

11. SPARQL endpoints might bring
high costs for possibly low gain.
server
“Fine, we’ll publish a data dump.”
Data dumps don’t allow
Web applications on live data.
You already provide data for free,
is it realistic to pay for users’ queries, too?

12. There’s more to Linked Data publishing
than just the two extremes.
data
dump
SPARQL
endpoint
high server efforthigh client effort
Triple Pattern
Fragments
server

13. Future Linked Data publishing:
simple servers, clever clients.
client server
?person a dbpedia-owl:Writer.
Triple Pattern
Fragments

14. Triple Pattern Fragment servers
cannot work hard, by definition.
server
highly reusable requests
high cacheability
low per-request processing cost

15. Complex queries are efficiently
executed on the client-side.
client
SELECT * WHERE {
?person a dbpedia-owl:Writer;
rdfs:label ?name;
dbpedia-owl:almaMater dbpedia:Trinity_College_Dublin.
}
Query now at fragments.dbpedia.org.
In your browser—in pure JavaScript!

16. About DBpedia’s fragments
Usage analysis so far
Fragments in the future

17. data (paged)
controls (other fragments)
metadata (total count)

18. Pingdom
155.702
Chrome
285.385
GoogleBot
332.177
TPF Client
3.219.756
The Client for Node.js is leading,
but other bots (and humans) follow.

19. JSON
2.867
283.035
HTML
316.183
TriG
833.341
Turtle
2.810.532
(anything)
Turtle has been most popular,
but TriG will lead soon.

20. Expired
164.105
Hit
1.249.571
Miss
2.838.720
More than a fourth of all requests
was served directly from the cache.

21. Oct 2014 Nov 2014 Dec 2014 Jan 2015 Feb 2015
267.196
1.038.867
357.305
2.433.045
157.805
in 4 days
17 Oct 2014 – 4 Feb 2015
November was a very busy month;
but February might top that!

22. “Type“ fragments were most common,
then “all”, and specific subclasses.
?s rdf:type ?o ?s ?p ?o <s> rdfs:subClassOf ?o
111.773
148.411
155.706

23. DBpedia fragments had 99.99% uptime,
having < 5 mins downtime per month.
1 request every minute by Pingdom
20 did not return
5 of which due to planned maintenance

24. About DBpedia’s fragments
Usage analysis so far
Fragments in the future

25. We plan to extend the interface
with features that improve querying.
data
dump
SPARQL
endpoint
high server efforthigh client effort
Triple Pattern
Fragments

26. APPS
No more excuses—start building!
DBpedia is queryable and 99.9% up.
It’s time to make
on top of live DBpedia data.

27. Instead of making apps with Web APIs
we’ll build apps from Linked Data.
APPS
WEB
on top of live DBpedia data.

28. Dublin
SPARQL
endpoint
Dublin
The classical approach:
we ask, we wait, we act.

29. Dublin DublinDublin
The Web approach:
we ask—and act as results arrive.

30. by iMinds – Ghent University

31. by Michael Luggen

32. your app?
client = new ldf.FragmentsClient('http://fragments.dbpedia.org/2014/en');
stream = new ldf.SparqlIterator(query, { fragmentsClient: client });
stream.on('data', doSomethingNice);
easy & realistic
3 lines of JavaScript
& fun

33. fragments.dbpedia.org
@RubenVerborgh