Table Of ContentManolis Koubarakis Giorgos Stamou
Giorgos Stoilos Ian Horrocks
Phokion Kolaitis Georg Lausen
Gerhard Weikum (Eds.)
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Reasoning Web
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10th International Summer School 2014
Athens, Greece, September 8–13, 2014
Proceedings
123
Lecture Notes in Computer Science 8714
CommencedPublicationin1973
FoundingandFormerSeriesEditors:
GerhardGoos,JurisHartmanis,andJanvanLeeuwen
EditorialBoard
DavidHutchison
LancasterUniversity,UK
TakeoKanade
CarnegieMellonUniversity,Pittsburgh,PA,USA
JosefKittler
UniversityofSurrey,Guildford,UK
JonM.Kleinberg
CornellUniversity,Ithaca,NY,USA
AlfredKobsa
UniversityofCalifornia,Irvine,CA,USA
FriedemannMattern
ETHZurich,Switzerland
JohnC.Mitchell
StanfordUniversity,CA,USA
MoniNaor
WeizmannInstituteofScience,Rehovot,Israel
OscarNierstrasz
UniversityofBern,Switzerland
C.PanduRangan
IndianInstituteofTechnology,Madras,India
BernhardSteffen
TUDortmundUniversity,Germany
DemetriTerzopoulos
UniversityofCalifornia,LosAngeles,CA,USA
DougTygar
UniversityofCalifornia,Berkeley,CA,USA
GerhardWeikum
MaxPlanckInstituteforInformatics,Saarbruecken,Germany
Manolis Koubarakis Giorgos Stamou
Giorgos Stoilos Ian Horrocks
Phokion Kolaitis Georg Lausen
Gerhard Weikum (Eds.)
Reasoning Web
Reasoning on the Web
in the Big Data Era
10th International Summer School 2014
Athens, Greece, September 8-13, 2014
Proceedings
1 3
VolumeEditors
ManolisKoubarakis
NationalandKapodistrianUniversityofAthens,Greece
E-mail:[email protected]
GiorgosStamou
GiorgosStoilos
NationalTechnicalUniversityofAthens,Zografou,Greece
E-mail:[email protected];[email protected]
IanHorrocks
UniversityofOxford,UK
E-mail:[email protected]
PhokionKolaitis
UniversityofCalifornia,SantaCruz,CA,USA
E-mail:[email protected]
GeorgLausen
UniversityofFreiburg,Germany
E-mail:[email protected]
GerhardWeikum
MaxPlanckInstituteforInformatics,Saarbrücken,Germany
E-mail:[email protected]
ISSN0302-9743 e-ISSN1611-3349
ISBN978-3-319-10586-4 e-ISBN978-3-319-10587-1
DOI10.1007/978-3-319-10587-1
SpringerChamHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2014946916
LNCSSublibrary:SL3–InformationSystemsandApplication,
incl.Internet/WebandHCI
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Preface
Thisvolumecontainstutorialpaperspreparedforthe10thReasoningWebSum-
mer School (RW 2014) held during September 8–13, 2014, in Athens, Greece.
The Reasoning Web series of annual summer schools started in 2005 by the
EuropeanNetworkofExcellenceREWERSE.Since2005,theschoolhasbecome
the prime educational event in the field of reasoningtechniques onthe Web, at-
tracting both young and established researchers.The 2014 edition of the school
was organized by the Department of Informatics and Telecommunications, Na-
tional and Kapodistrian University of Athens (Prof. Manolis Koubarakis) and
the Institute for Communication and Computer Systems of the National Tech-
nical University of Athens (Prof. Giorgos Stamou and Dr. Giorgos Stoilos). As
with previous editions, this year’s summer school was co-located with the 8th
International Conference on Web Reasoning and Rule Systems (RR 2014).
The research area of the Semantic Web and Linked Data has been covered
comprehensively by recent editions of the Reasoning Web Summer School since
many advanced capabilities required by Semantic Web and Linked Data appli-
cation scenarios call for reasoning. In 2014, the theme of the school was:
“Reasoning on the Web in the Big Data Era.”
Theinventionofnewtechnologiessuchassensors,socialnetworksplatforms,
and smart phones has enabled organizationsto tap a huge amount of data that
traditionally has not been available to them, and to combine it with in-house
proprietary data. At the same time, enabling technologies (e.g., elastic cloud
computing platforms) have made strong progress enabling the implementation
ofdatamanagementandknowledgediscoverytechniquesthatworkonterabytes
or petabytes of data. In 2014, the lecture programof the Reasoning Web school
reflected this industrial reality, and introduced students to recent advances in
Big Data aspects of Semantic Web and Linked Data, and the fundamentals of
reasoning techniques that can be used to tackle Big Data applications.
The tutorial papers are in-depth surveys of the research topics covered in
lectures by the distinguished invited speakers of the school. They have been
written as accompanying material for the students of the summer school, to
deepentheirunderstandingandtoserveasareferenceforfurtherdetailedstudy.
The accompanying lecture slides of all tutorials are available on the summer
school web-site: http://rw2014.di.uoa.gr/.
We would like to thank everybody who made this event possible. First and
foremost,thepresentersofthelecturesandtheirco-authors.Secondly,themem-
bers of our scientific advisory board (Profs. Ian Horrocks, Phokion Kolaitis,
Georg Lausen, and Gerhard Weikum) and our reviewers. We are thankful for
their advice and feedback and their timely reviews of the papers. Furthermore,
wewouldliketothankthelocalorganizationteamattheNationalandKapodis-
trian University of Athens and the Institute for Communication and Computer
VI Preface
Systems, especially Kalliroi Dogani, Maria Karpathiotaki, Lydia Themeli, and
Eleni Iskou.We wouldalsolike to thank oursponsors:the Artificial Intelligence
journal, the European project Optique (http://www.optique-project.eu/),
the National Science Foundation (NSF), the Institut national de recherche en
informatique et en automatique (Inria), the Hellenic Artificial Intelligence Soci-
ety (EETN), ORACLE Greece, Siemens, and Google Inc.
Last but not least, we would like to thank the chairs of RR 2014, Prof.
Axel Polleres, Dr. Roman Kontchakov, Prof. Marie-Laure Mugnier, and Prof.
Francesco Ricca for a great collaboration in putting together all the details of
the two events.
June 2014 Manolis Koubarakis
Giorgos Stamou
Giorgos Stoilos
Organization
Organizing Chairs
Manolis Koubarakis National Kapodistrian University of Athens,
Greece
Giorgos Stamou National Technical University of Athens,
Greece
Giorgos Stoilos National Technical University of Athens,
Greece
Scientific Advisory Board
Ian Horrocks University of Oxford, UK
Phokion Kolaitis University of California, Santa Cruz, USA
Georg Lausen University of Freiburg, Germany
Gerhard Weikum MaxPlanckInstituteforInformatics,Germany
Website Administrators
Kalliroi Dogani National Kapodistrian University of Athens,
Greece
Maria Karpathiotaki National Kapodistrian University of Athens,
Greece
Local Organization
Lydia Themeli National Kapodistrian University of Athens,
Greece
Eleni Iskou National Technical University of Athens,
Greece
Additional Reviewers
Giannakopoulou, Asimina Tsalapati, Eleni
Trivela, Despoina
VIII Organization
Sponsors
Table of Contents
Linked Open Data
Introduction to Linked Data and Its Lifecycle on the Web............. 1
Axel-Cyrille Ngonga Ngomo, S¨oren Auer, Jens Lehmann, and
Amrapali Zaveri
An Introduction to Question Answering over Linked Data............. 100
Christina Unger, Andr´e Freitas, and Philipp Cimiano
RDF and Graph Databases
Query Processing for RDF Databases............................... 141
Zoi Kaoudi and Anastasios Kementsietsidis
Introduction to Graph Databases .................................. 171
Josep Llu´ıs Larriba-Pey, Norbert Mart´ınez-Baz´an, and
David Dom´ınguez-Sal
Description Logic Based Ontologies
An Introduction to Description Logics and Query Rewriting........... 195
Roman Kontchakov and Michael Zakharyaschev
An Introduction to Ontology-BasedQuery Answering with Existential
Rules........................................................... 245
Marie-Laure Mugnier and Micha¨el Thomazo
Ontology Based Data Access on Temporal and Streaming Data ........ 279
O¨zgu¨r Lu¨tfu¨ O¨z¸cep and Ralf M¨oller
Applications
Querying and Learning in Probabilistic Databases.................... 313
Maximilian Dylla, Martin Theobald, and Iris Miliaraki
Semantic and Reasoning Systems for Cities and Citizens .............. 369
Spyros Kotoulas
Author Index.................................................. 389
Introduction to Linked Data and Its Lifecycle
on the Web
Axel-CyrilleNgongaNgomo,SörenAuer,JensLehmann,andAmrapaliZaveri
AKSW,InstitutfürInformatik,UniversitätLeipzig,Pf100920,04009Leipzig
[email protected]
http://aksw.org
Abstract. WithLinkedData,averypragmaticapproachtowardsachievingthe
visionoftheSemanticWebhasgainedsometractioninthelastyears.Theterm
LinkedDatareferstoasetofbestpracticesforpublishingandinterlinkingstruc-
tureddataontheWeb.Whilemanystandards,methodsandtechnologiesdevel-
oped within by the Semantic Web community are applicable for Linked Data,
there are also a number of specific characteristics of Linked Data, which have
tobeconsidered.InthisarticleweintroducethemainconceptsofLinkedData.
WepresentanoverviewoftheLinkedDatalife-cycleanddiscussindividualap-
proachesaswellasthestate-of-the-artwithregardtoextraction,authoring,link-
ing,enrichmentaswellasqualityofLinkedData.Weconcludethechapterwitha
discussionofissues,limitationsandfurtherresearchanddevelopmentchallenges
of Linked Data. Thisarticleis an updated version of a similar lecture given at
ReasoningWebSummerSchool2013.
1 Introduction
Oneofthebiggestchallengesintheareaofintelligentinformationmanagementisthe
exploitationoftheWebasaplatformfordataandinformationintegrationaswellasfor
searchandquerying.JustaswepublishunstructuredtextualinformationontheWebas
HTMLpagesandsearchsuchinformationbyusingkeyword-basedsearchengines,we
arealreadyabletoeasilypublishstructuredinformation,reliablyinterlinkthisinforma-
tionwithotherdatapublishedontheWebandsearchtheresultingdataspacebyusing
moreexpressivequeryingbeyondsimplekeywordsearches.TheLinkedDataparadigm
has evolved as a powerfulenabler for the transition of the currentdocument-oriented
Web intoa Web ofinterlinkedData and,ultimately,into theSemanticWeb. Theterm
LinkedData herereferstoa setofbestpracticesforpublishingandconnectingstruc-
tureddataontheWeb.Thesebestpracticeshavebeenadoptedbyanincreasingnumber
ofdataprovidersoverthepastthreeyears,leadingtothecreationofaglobaldataspace
thatcontainsmanybillionsofassertions–theWebofLinkedData(cf.Figure1).
In this chapter we give an overview of recent development in the area of Linked
Datamanagement.Thedifferentstagesinthelinkeddatalife-cycle[11]aredepictedin
Figure2.Informationrepresentedinunstructuredformoradheringtootherstructured
orsemi-structuredrepresentationformalismsmustbe mappedto theRDF datamodel
(Extraction).OncethereisacriticalmassofRDFdata,mechanismshavetobeinplace
to store, indexand querythis RDF data efficiently(Storage& Querying).Users must
M.Koubarakisetal.(Eds.):ReasoningWeb2014,LNCS8714,pp.1–99,2014.
(cid:2)c SpringerInternationalPublishingSwitzerland2014
