Streaming Linked Data: From Vision to Practice

170 Pages·2023·11.788 MB·English

by  Riccardo Tommasini, Pieter Bonte, Fabiano Spiga, Emanuele Della Valle

Riccardo Tommasini
Pieter Bonte
Fabiano Spiga
Emanuele Della Valle
Streaming
Linked
Data
From Vision to Practice
Streaming Linked Data
Riccardo Tommasini • Pieter Bonte (cid:129)
Fabiano Spiga (cid:129) Emanuele Della Valle
Streaming
Linked
Data
From Vision to Practice
RiccardoTommasini PieterBonte
LIRISLab DepartmentofInformationTechnology
InstitutNationaldesSciencesAppliquées GhentUniversity
Villeurbanne,France Ghent,Belgium
FabianoSpiga EmanueleDellaValle
Tallinn,Estonia DepartmentofElectronics,Informaticsand
Bioengineering
PolitecnicodiMilano
Milano,Italy
ISBN978-3-031-15370-9 ISBN978-3-031-15371-6 (eBook)
https://doi.org/10.1007/978-3-031-15371-6
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To myfamily,who always supportedmein
myjourney,and tothosewho sawthe
potentialina roughstoneandhelppolishing
itstalent.Inparticular,toSherifSakr(R.I.P.)
-Riccardo
To mylovingwifeandbeautifuldaughters,
mysourcesof inspiration.Thankyou for
accompanyingmealongmypath.
-Pieter
To mynieceSofiaandto allthechildrenof
thisworldnotsuitableforchildren,who
inspiremen ofgoodwill tomakeita better
place.
-Fabiano
To mywifeSimonaand ourwonderful
daughterGiulia.PantaRei,thusseizethe
day.
-Emanuele
Foreword
Nomatterwhatareaofknowledgewemaybetalkingabout,itisalwaysachalleng-
ing task to compile into a single book the most relevant knowledge accumulated
during more than a decade of active research and application. Indeed, this books
compilesandsummarizesintoacoherentstorylinetheworkthatwasinitiatedmore
than10yearsagobyagroupofresearcherswhohadalreadyembracedtheSemantic
Webprinciplesandconceptstodealwiththevarietyofdataandidentifiedtheneed
to startaddressingthose aspectsrelatedtothe velocityofdatain manyreal-world
contexts.
Havingbeenpartofthiscommunitysinceitsearlystages,includingthesupervi-
sionofPhDstudentsandotherearly-stageresearchers,andhavingcollaboratedwith
someoftheauthorsofthisbook,aswellasmanyotherswhoseworksarereferenced
init,ImustadmitthatIalwaysfounditdifficulttocollectinasinglefolderallthe
relevantreference materials that I should be providingto the next PhD student in
thistopicortomystudentsatthevariousresearchmastersonArtificialIntelligence
and Data Science that I participate in. Rooted on the work done for many years
in tutorials around the topics of stream reasoning, RDF stream processing, and
Streaming Linked Data, this book provides a clear solution for this problem and
willbecomeoneofthekeyreferencesinmycoursesaroundSemanticWebtopics.
Iwanttoemphasizeherethatthisisnotjustabookthatcompilesdisconnected
piecesofresearch.Bytakingaquicklookatthetableofcontents,thereaderswill
immediatelyrealizethattheauthorshavegonefarbeyondgeneratinganincremental
compendiumoftheresearchworksthathavebeendoneovertheyears,whatwould
berelativelyeasyandwouldrequirelittleeffort.Theyhavecreatedacoherentstory
wherereaderswillfirstbeabletounderstandtheprinciplesonwhichthisresearch
areahasbeenestablished(aroundtheaspectsrelatedtovarietyandvelocity).Then
they will be able to browse and learn fromthe historical evolutionof approaches,
wellrootedontheoryandpractice.Theywilllaterunderstandwhatisthelifecycle
ofstreaminglinkeddataprojectsandinitiatives, basedonthe experiencegathered
bytheauthorsinnumerousprojects.Andfinallytheywillunderstandwhichefforts
have been done for the evaluation and continuousimprovementof the theoretical
frameworksanddevelopmentsystemsaroundthisarea.Allofthiswillprovidethose
vii
viii Foreword
interested in getting up to speed into the world of streaming linkeddata to have a
singlesourceofreference.
AndIamespeciallyhappywhenseeingthelatestchapterwiththeexercisebook,
something that in many situations we forget about when we are creating a book
thatmaynotonlybeusedasareferencebookforresearchersbutalsoasaninitial
textbookforpractitioners.Iwilldefinitelyusealsothecontentsofthefinalchapter,
theexercisebook,withmyMasterstudents.
Insummary,Irecommendthisbooktoallthoseinterestedinunderstandinghow
a semantic-basedapproach(andits correspondingtechnologies)can be appliedin
contextsthatgobeyondstaticdata,eitherbecausetheywanttostartapplyingthese
techniquesinpracticeorbecausetheyareinterestedinpursuingresearchinthearea.
AndIalsorecommenditforthoselikemewhoareteachingstudentsattheMaster
levelandwanttoprovidethemwithanadvancedtextbookonatopicforwhichthere
wasnotsuchcompiledmaterialbefore.
Madrid,Spain OscarCorcho
June2022 OntologyEngineeringGroup
R&DCenterforArtificialIntelligence(AI.nnovationSpace)
UniversidadPolitécnicadeMadrid
Preface
A fruitfulsequence of tutorials prompteda rationalizationof the research journey
that,across10years,shepherdedseveralresearchersandledtonumerouscontribu-
tions.In2008,whentheStreamReasoningresearchquestionwasfirstlyenvisioned,
datavelocitywasstartingtoemerge.Highlydynamicresourcesdidnotyetpopulate
the Web, but social networks and the Internet of Things pushed toward real-time
datamanagement.WiththeLargeKnowledgeCollider(LarKC)project,thevision
becameacommunity,whichgainedanidentitywithintheSemanticWebcontext.
The second generation of researchers developed Stream Reasoning into RDF
Stream Processing. Seminalcontributionsstrengthenthe theoreticalfoundationof
thefield,whichexpandedbeyondtheSemanticWebborderstomixwithinductive
anddeductiveartificialintelligence.StreamReasoningcannowcountcontributions
in(Temporal)logic,Robotics,MachineLearning,anddataintegration.
RDF Stream Processing ultimately led to Streaming Linked Data, which this
book is about. While the third generation of stream reasoning researchers is
approachingseniority,bestpracticesareemerging,andstreamprocessingisrising
astheindustry’sdefactostandardforBigDataengineeringandanalytics.
Thisbookwas envisionedas a resourcethatcollectsresearcheffortsandcould
guidethenextgenerationofresearchers,practitioners,andindustrialstakeholders.
Our goal is to explain the value of data integration when it does not neglect the
time-varyingnatureofdataandthecontinuousessenceofsomeinformationneeds.
Thisvolumefocusesontheoreticalandpracticalaspects. Itprovidesa compre-
hensive perspective of algorithms, systems, and applications for streaming linked
data. Finally, it introduces the readers to RSP4J, a novel open-source project that
aimstogathercommunityeffortsinsoftwareengineeringandempiricalresearch.
An introductory chapter positions the work by explaining what motivates the
designof specific techniquesfor processingdata streamsusing Web technologies.
Theprerequisitechapterbrieflysummarizesthenecessarybackgroundconceptsand
models needed to understand the remaining content of the book. Subsequently,
Chap.3 focuses on processing RDF streams, taming data velocity in an open
environment characterized by high data variety. It introduces query answering
algorithms with RSP-QL and analytics functions over streaming data. Chapter 4
ix
x Preface
focuses on publishing streams and events on the Web as a prerequisite aspect
to make data findable and accessible to applications. Chapter 5 touches on the
problemsofbenchmarkingsystemsthatanalyzeWebstreamstofostertechnological
progress.Itsurveysexistingbenchmarksandintroducesguidelinesthatmaysupport
new practitioners in approaching the issue of continuous analytics. Chapter 6
presentsalistofexamplesandexercisesthatwillhelpwhoeverapproachesthearea
togetusedtoitspracticesandbecomeconfidentinitstechnologicalstack.
This book provides a comprehensive overview of core concepts and techno-
logicalfoundationsof continuousanalyticsof Web streams. Itpresentsreal-world
examplesandnamessystemsandapplications.Therefore,itisofparticularinterest
to students, lecturers, and researchers in Web data management and stream data
management.
In practice, this book would not have been possible withoutseveral people:(i)
the authors, who are linked by more than just respect and professional apprecia-
tion; their research groups, namely, Marco Balduini, Daniele Dell’Aglio, Femke
Ongenae, Alessandro Margara, Ahmed Awad, and Radwa ElShawi; and their
collaboratorswithinthestreamreasoningcommunity,whocontributedtothevision
scientifically, i.e., Jean-Paul Calbimonte, Danh LePhouc, Robin Kerskisa¨rkka,
¨
Oscar Corcho, Alessandra Mileo, Ali Intizar, Jacopo Urbani, Boris Motik, Darko
Anicic,ThomasEiter,PatrikSchneider,andmanymanymore.
Thegenesisofthisbookdatesbacktotheendof2019.Aseriesofunfortunate
events,includingCOVID-19andtheprematuredemiseofProf.SherifSakr,1 slow
downthewritingprocess.Yet,wearegladtopresentthisworktothecommunity.
Lastbutnotleast,wethankourinstitutions,INSALyonandLIRISLab,Ghent
UniversityIMEC,PolitecnicodiMilano,andtheUniversityofTartu.Inparticular,
Riccardo Tommasini and Fabiano Spiga acknowledge support from the European
Social Fund via IT Academy program. Pieter Bonte acknowledges his support
from Research Foundation Flanders (FWO) through his postdoctoral fellowship
(1266521N).
Lyon,France RiccardoTommasini
Gent,Belgium PieterBonte
Tartu,Estonia FabianoSpiga
Milan,Italy EmanueleDellaValle
April2022
1RestinPeace.
Contents
1 GeneralIntroduction........................................................ 1
1.1 WebStreamProcessingatGlance...................................... 4
1.2 TheColorWaveRunningExample..................................... 5
1.3 RDFStreamProcessingwithRSP4J................................... 7
1.3.1 ChallengesandRequirements.................................. 8
1.3.2 RSP4J’sArchitecture........................................... 10
1.4 HowtoReadThisBook ................................................ 11
1.5 Outline................................................................... 13
References..................................................................... 13
2 Preliminaries ................................................................. 17
2.1 Introduction ............................................................. 17
2.2 DataVelocity............................................................ 18
2.2.1 DataStreamsandContinuousQueries......................... 18
2.2.2 RelationalStreamProcessing .................................. 21
2.2.3 StreamProcessingEngines..................................... 24
2.2.4 ComplexEventProcessing..................................... 27
2.3 DataVariety............................................................. 28
2.3.1 RDFandRDFSchema ......................................... 29
2.3.2 ReasoningTechniques.......................................... 32
2.3.3 WebOntologyLanguage....................................... 34
2.3.4 SPARQLProtocolandRDFQueryLanguage ................ 35
2.4 ChapterSummary....................................................... 38
References..................................................................... 39
3 TamingVarietyandVelocity................................................ 41
3.1 Introduction ............................................................. 41
3.2 RDFStreamProcessing................................................. 42
3.2.1 FromCQLtoRSP-QL ......................................... 42
3.2.2 RSP-QLQueryLanguage...................................... 47
3.2.3 ReportingStrategies............................................ 47
xi