Introduction to the USEWOD2012 workshop at WWW2012, Lyon, France. Some background, motivation, statistics, potential problems.

1. USEWOD2012
History and Background of the
USEWOD Data Challenge
Knud Möller, Talis Systems Ltd.
@knudmoeller
1

2. Möller, K., Hausenblas, M., Cyganiak,
R., Grimnes, G., and Handschuh, S.
(2010). Learning from linked open
data usage: Patterns & metrics. In
WebScience 2010, Raleigh, NC, USA.
http://journal.webscience.org/302/
2

3. Linked Data
Conventional “Eye-ball” Web Web of Linked Data
interlinked documents interlinked items of data
(URIs, RDF)
mainly people / Web mainly machine agents (but
browsers also people?)
3

4. Linked Data
Conventional “Eye-ball” Web Web of Linked Data
interlinked documents interlinked items of data
(URIs, RDF)
mainly people / Web mainly machine agents (but
browsers also people?)
3

5. How is Linked Data being
used?
• plenty of research on conventional Web
usage
• what about usage of linked data?
Why?
• how healthy is the Web of linked data?
• who is using the data and how? Is it useful?
Are there trends?
• providers: improve hosting
• ... just curiosity! 4

6. Approach
particular sites:
– a URI for each data item ➙ a request for each data item
(resource)
– content negotiation best practices
– redirection (HTTP 303)
5

7. Approach
particular sites:
– a URI for each data item ➙ a request for each data item
(resource)
– content negotiation best practices
– redirection (HTTP 303)
http://data.semanticweb.org/
conference/www/2009
plain
resource URI
RDF HTML
document URI document URI
http://data.semanticweb.org/ http://data.semanticweb.org/
conference/www/2009/rdf conference/www/2009/html 5

8. Approach (ctd.)
• server log files
– common log format (CLF), combined log format
Request IP Request Date Request String
80.219.211.147 - - [23/May/2009:09:52:03 +0100] "GET /sparql?query=PREFIX [..] LIMIT+200 HTTP/1.0"
200 64674 "-" "ARC Reader (http://arc.semsol.org/)"
Response Code Responce Size Referrer User Agent
• RDF requests vs. “semantic” requests
•90.21.243.141 − − [06/Oct/2008:16:07:58 +0100] ”GET /organization/vrije
−universiteit−amsterdam−the−netherlands HTTP/1.1” 303 7592 ”−” ”rdflib
−2.4.0 (http://rdflib.net/; eikeon@eikeon.com)”
•90.21.243.141 − − [06/Oct/2008:16:08:02 +0100] ”GET /organization/vrije
−universiteit−amsterdam−the−netherlands/rdf HTTP/1.1” 200 453586 ”−” ”rdflib
−2.4.0 (http://rdflib.net/; eikeon@eikeon.com)”

9. 219.211.147 - - [23/May/2009:09:52:03 +0100] "GET /sparql?query=PREFIX [..] LIMIT+200 HTTP/1.0"
200 64674 "-" "ARC Reader (http://arc.semsol.org/)"
nse Code Responce Size Referrer
Source Data
User Agent
Figure 1: The combined log format
# triples # days total # hits # plain hits # RDF hits # HTML hits SPARQL
Dog Food 79,175 597 8,427,967 1,923,945 259,031 1,647,205 879,932
(14,117) (3,223) (434) (2,759) (1,471)
DBpedia 109,750,000 118 87,203,310 22,821,475 7,008,310 22,999,237 20,972,630
(739,011) (193,402) (59,392) (194,909) (177,734)
DBTune 74,209,000 61 7,467,125 1,952,185 1,135,509 677,904 3,055,493
(122,412) (32,003) (18,615) (11,113) (50,090)
RKBExplorer 91,501,684 29 529,938 — — — 9,327
(18,274) (—) (—) (—) (322)
RDF 5.8% Semantic 2.8% Table RDF 14.9% Semantic 4.2% datasets
1: Overview of four LOD RDF 7.8% Semantic 2.5%
s are served. For our evaluation, we had access to log
Plain 47.7%
taining a SPARQL query, we assume that it is
Plain 45% Plain 41.0%
two periods: from 24/05/2009–21/06/2009 and from ble of handling the query result, i.e., either a
/2009–29/10/2009, i.e., roughly two months. bindings (in the case of a SELECT query), pote
containing URIs of RDF resources, or an RDF
RKBExplorer (in the case of a CONSTRUCT or DESCRIBE q
BExplorer6 [11] is another meta-dataset currently com-
HTML 46.5% HTML 39.9%
44 sub-datasets covering various topics and sources • RDF requests: if an agent directly requests
HTML 51.1%
the domain of academic research, as well as a Web from a server, we assume that it knows how t
ation that allowsDBpedia
users to access and browse its content cess data in this format. 7 Directly here mean
DBTune the agent specified an RDF syntax such as r
Dog Food
ntegrated fashion. Both RDF and HTML documents
the resources in all datasets are available. Apart from as an acceptable response in the header of its re

10. Agents
http://data.semanticweb.org, 21/07/2008 - 20/06/2009
500000
hits
3)
83
66 8
97 ordinary traffic: the usual suspects
37 23
)
(4
13 59
400000
ot
(1
eB
rp
)
28
gl
lu
&
)
11
89
oo
!S
92
11
G
oo
(1
t(
h
300000
bo
er
5)
Ya
32
ch
sn
12
et
m
hits
eF
r(
le
ic
w
nd
ra
Si
200000
)
tic
42
ul
3
8)
(7
m
80
.0
(6
/1
r
ot
de
fb
100000
ea
rd
R
C
R
A
0 8
0 5 10 15 20 25 30
agents

11. semantic hits/total hits (>100 semantic hits)
0
0.2
0.4
0.6
0.8
1
attributor/1.13.2
triplr
sindicebot
rdflib-2.4.2
Ripple
OL_Virtuoso_RDF_crawler
Morph_Converter_Service
Falconsbot
Speedy
Slug_SW_Crawler
yacybot
hclsreport-crawler
MJ12bot
PycURL
heritrix/1.14.3
SindiceFetcher
heritrix/pom.version
heritrix/2.0.2
multicrawler
SindiceBot
ia_archiver
Zitgist-APlusPlus-Agent
rdflib-2.4.1
they?
Mp3Bot
curl
Zend_Http_Client
Speedy_Spider
nxcrawler
marbles
-
Java
rdflib-2.4.0
(unknown)
ARC_Reader
MLBot
Mozilla
Jakarta_HttpClient
9
Wget
libwww-perl
MSIE
Firefox
Python-urllib
sindice_ontology_fetcher
Agents: How “semantic” are
Googlebot

12. Demand for LOD?
DBpedia Hits over Time (smoothing factor 0.05)
300000
plain
html
rdf
250000 semantic
200000
150000
100000
no increase for semantic requests
50000
0
2009-06-20
2009-07-04
2009-07-18
2009-08-01
2009-08-15
2009-08-29
2009-09-12
2009-09-26
2009-10-10
2009-10-24
2009-11-07
10

13. Impact of Real-world
Events
Irish Lisbon Treaty Referendum (smoothing factor 0.05)
9
http://dbpedia.org/resource/Republic_of_Ireland
http://dbpedia.org/resource/European_Union
8 http://dbpedia.org/resource/Treaty_of_Lisbon
7
possible impact
6
5
4
3
2
1
0
2009-06-20
2009-07-04
2009-07-18
2009-08-01
2009-08-15
2009-08-29
2009-09-12
2009-09-26
2009-10-10
2009-10-24
2009-11-07
11

14. Impact of Real-world
Events
Michael Jackson Memorial Service (smoothing factor 0.05)
4.5
http://dbpedia.org/resource/Staples_Center
http://dbpedia.org/resource/Michael_Jackson_memorial_service
4 http://dbpedia.org/resource/Michael_Jackson
3.5
3
2.5
2
1.5
possible impact
1
0.5
0
2009-06-20
2009-07-04
2009-07-18
2009-08-01
2009-08-15
2009-08-29
2009-09-12
2009-09-26
2009-10-10
2009-10-24
2009-11-07
12

15. • this research: one motivation for
USEWOD
• expand the dataset, encourage more
and different analyses
13

16. USEWOD Data Challenge 2012
2nd International Workshop on Usage Analysis
and the Web of Data
Sponsored by the LATC project

17. USEWOD Data Challenge

18. USEWOD Data Challenge
Moving forward by releasing a dataset:
• to relieve difficulty of obtaining real-life usage
data
• to allow comparison and combination of
approaches done on the same dataset
• by releasing a relatively new type of logs: usage
on the Web of Data.

19. USEWOD Data Challenge
Moving forward by releasing a dataset:
• to relieve difficulty of obtaining real-life usage
data
• to allow comparison and combination of
approaches done on the same dataset
• by releasing a relatively new type of logs: usage
on the Web of Data.
Also for longer-term use.

20. The USEWOD Dataset 2011
Server logs from two major web of data
servers:
• DBPedia
• Several weeks during 2 months of requests
• Semantic Web Dog Food
• 2 years of requests from Dec 2008 – Dec 2010

21. USEWOD 2011 Challenge
Participants

22. USEWOD 2011 Challenge
Participants
• At the time of the workshop 11 groups had
requested the 2011 data

23. USEWOD 2011 Challenge
Participants
• At the time of the workshop 11 groups had
requested the 2011 data
• By now 28.

24. USEWOD 2011 Challenge
Participants
• At the time of the workshop 11 groups had
requested the 2011 data
• By now 28.
• 7 data challenge paper submissions

25. USEWOD 2011 Challenge
Participants
• At the time of the workshop 11 groups had
requested the 2011 data
• By now 28.
• 7 data challenge paper submissions
• Winner of the 2011 USEWOD data challenge prize:
• Mario Arias Gallego, Javier D. Fernández, Miguel A.
Martínez-Prieto and Pablo De La Fuente. An Empirical
Study of Real-World SPARQL Queries.

26. USEWOD 2011 Challenge
Participants
• At the time of the workshop 11 groups had
requested the 2011 data
• By now 28.
• 7 data challenge paper submissions
• Winner of the 2011 USEWOD data challenge prize:
• Mario Arias Gallego, Javier D. Fernández, Miguel A.
Martínez-Prieto and Pablo De La Fuente. An Empirical
Study of Real-World SPARQL Queries.

27. The USEWOD Dataset 2012
Server logs from two major web of data
servers:
• DBPedia
• Several weeks during 2 months of requests
• Semantic Web Dog Food
• 2 years of requests from Dec 2008 – Dec 2010
• Linked Open Geo Data
• Bio2RDF

28. USEWOD 2012 Challenge
Participants
• 20 groups requested the data, so far.
• 2 data challenge paper submissions…
• 1 winner of the USEWOD data
challenge prize.
• kindly brought to you by LATC

29. DBpedia

30. DBpedia

31. DBpedia

32. DBpedia

33. Semantic Web Dog Food
[Screenshots and image take from http://data.semanticweb.org/]

34. Semantic Web Dog Food
[Screenshots and image take from http://data.semanticweb.org/]

35. Semantic Web Dog Food
[Screenshots and image take from http://data.semanticweb.org/]

36. Requests for Human / Machine
readable Web data
Both servers get requests for RDF
• http://dbpedia.org/data/Berlin.rdf
as well as HTML
• http://dbpedia.org/page/Berlin
And requests for the URI itself:
• http://dbpedia.org/resource/Berlin (will be
served HTML or RDF)

37. Requests to SPARQL endpoints
• Both servers have a SPARQL endpoint
to request RDF data:
SELECT DISTINCT ?s ?t ?y ?to ?h
WHERE {
?s dc:title ?t .
?s swrc:year ?y .
OPTIONAL {?s foaf:homepage ?h }.
OPTIONAL {?s foaf:topic ?t }
}
order by desc(?y”)
LIMIT 200

38. Anonymizing the USEWOD
Dataset

39. Anonymizing the USEWOD
Dataset
• IP addresses:
• replace all IPs with 0.0.0.0
• add the country code for the original IP
address -> track location of requests
• add an identifier of the original IP -> track
individual requestors

40. USEWOD2011, Hydebarabad,
India
• M. Kirchberg, R. K. L. Ko, and B. S.
Lee. From linked data to relevant data
- time is the essence. - http://
arxiv.org/abs/1103.5046
• M. A. Gallego, J. D. Fernández, M. A.
Martínez-Prieto, and P. D. L. Fuente.
An empirical study of real-world
SPARQL queries. - http://arxiv.org/
abs/1103.5043 25

41. USEWOD2012, Lyon, France
• A. Raghuveer. Characterizing Machine
Agent Behavior through SPARQL Query
Mining. - http://ir.ii.uam.es/
usewod2012/
usewod2012_raghuveer.pdf
• J. Hoxha, M. Junghans, S. Agarwal.
Enabling Semantic Analysis of User
Browsing Patterns in the Web of Data.
- http://arxiv.org/abs/1204.2713
26

42. What could be improved?
• does not work well with embedded metadata (e.g.,
RDFa-based sites)
• does not take into account usage through meta sites
(indexes, search engines, mirrors, ...)
• does (probably) not take into account usage through
apps
• what about caches?
• what about bulk/dump downloads of data?
• not enough usage to be interesting yet? 27