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MOMIS: Exploiting agents to support information integration / G. Cabri; F. Guerra; M. Vincini; S. Bergamaschi; L.Leonardi; F. Zambonelli. - In: INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS. - ISSN0218-8430. - STAMPA. - 11:3-4(2002), pp. 293-313.
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MOMIS: Exploiting agents to support information integration
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PublishedDOI:10.1142/S0218843002000601
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This is the peer reviewd version of the followng article:
Exploiting Agentsto Support Inf ormation Integration
G. Cabri�, F. Guerra
�, M. Vincini
�, S.Bergamaschi
���, L. Leonardi
�, andF. Zambonelli
�
e-mail:�cabri.giacomo,guerra.francesco,vincini.maurizio,
bergamaschi.sonia,leonardi.letizia,zambonelli.franco� @unimo.it
�Dipartimentodi Ingegneriadell’Informazione
Universit̀adi ModenaeReggioEmilia
Via Vignolese905,41100Modena�
CSITE-CNRBologna
V.le Risorgimento2, 40136Bologna�
Dipartimentodi ScienzeeMetodidell’Ingegneria
Universit̀adi ModenaeReggioEmilia
Via Allegri 13,42100ReggioEmilia
Abstract. Informationoverloadingintroducedby thelargeamountof datathatis spreadover theInter-
netmustbefacedin anappropriateway. Thedynamismandtheuncertaintyof theInternet,alongwith
theheterogeneityof thesourcesof informationarethetwo mainchallengesfor thetoday’s technologies
relatedto informationmanagement.In theareaof informationintegration,this paperproposesanap-
proachbasedonmobilesoftwareagentsintegratedin theMOMIS (MediatorenvirOnmentfor Multiple
InformationSources)infrastructure,whichenablessemi-automaticinformationintegrationto dealwith
theintegrationandqueryof multiple,heterogeneousinformationsources(relational,object,XML and
semi-structuredsources).The exploitationof mobileagentsin MOMIS cansignificantlyincreasethe
flexibility of thesystem.In fact,their characteristicsof autonomyandadaptabilitywell suit distributed
andopenenvironments,suchasthe Internet.The aim of this paperis to show the advantagesof the
introductionin theMOMIS infrastructureof intelligentandmobilesoftwareagentsfor theautonomous
managementandcoordinationof integrationandqueryprocessingoverheterogeneousdatasources.
1 Intr oduction
Informationin the Internetworld is spreadandhighly heterogeneous,andproviding an integratedaccess
to multiplesourcesis achallengingissueconcerningcooperationandinteroperabilityin globalinformation
systems.In thepast,companieshave equippedthemselveswith datastoringsystemsbuilding up informa-
tivesystemscontainingdatathatarerelatedoneanother, but whichareoftenredundant,heterogeneousand
not alwayssubstantial.The problemsthat have to be facedin this field aremainly dueto both structural
andapplicationheterogeneityof thesources,aswell asto thelackof acommonontology, causingsemantic
differencesbetweeninformationsources.Moreover, thesesemanticdifferencescancausedifferentkindsof
conflicts,rangingfrom simplecontradictionsin nameuse,to structuralconflicts.With respectto conven-
tional view integrationtechniques[4], in thelargescaletherearecomplicatingfactorsdueto thesemantic
heterogeneityof thesources.Therefore,to meettherequirementsof global,Internet-basedinformationsys-
tems,it is importantthatthetoolsdevelopedfor supportingtheseactivitiesaresemi-automaticandscalable
asmuchaspossible.
To facethe issuesrelatedto scalability in the large-scale,in this paperwe proposethe exploitation
of the MOMIS (MediatorenvirOnmentfor Multiple InformationSources)infrastructure,which focuses
on capturingandreasoningaboutsemanticaspectsof schemadescriptionsof heterogeneousinformation
sources,enhancedby theintegrationof mobileagentsfor supportingintegrationandqueryoptimization.
MOMIS [7,11,8,10] is an infrastructurefor information integration that dealswith the integration
andqueryof multiple, heterogeneousinformationsources,containingstructuredandsemistructureddata.
MOMIS is asupportsystemfor semiautomaticintegrationof heterogeneoussourcesschema(relational,ob-
ject,XML andsemistructuredsources);it carriesout integrationfollowing asemanticapproachwhichuses
Descriptionlogics-basedtechniques,clusteringtechniquesandan ODM-ODMG [21] extendedmodelto
representextractedandintegratedinformation,ODM � . UsingtheODL � language,referredto theODM �model,it is possibleto describethesources(localschema)andMOMIS supportsthedesignerin thegenera-
tion of anintegratedview of all thesources(GlobalVirtual View), whichis expressedusingXML standard.
Theuseof XML in thedefinitionof theGlobalVirtual View lets to useMOMIS infrastructurewith other
openintegrationinformationsystemsby theinterchangeof XML datafiles.
In a wideandopenenvironment,suchastheInternet,MOMIS suffersfrom somelimitationsrelatedto
theuncertaintyandtheunreliability intrinsic to large-scaleenvironments.Moreover, a bettermanagement
of the connectionsandthe exchangesof informationhelp MOMIS in saving network resources.The ex-
ploitationof mobileagentscanovercomesuchlimitationsandincreaseflexibility . In fact,they well suit the
requirementsof Internetapplicationsthanksto their characteristics.Theagency feature[31] permitsthem
to exhibit ahighdegreeof autonomywith regardto theusers:they try to carryout their tasksin aproactive
way, reactingto the changesof the environmentthey arehosted.The mobility feature[32] takesseveral
advantagesin awideandunreliableenvironmentsuchastheInternet.First,mobileagentscansignificantly
save bandwidth,by moving locally to the resourcesthey needandby carryingthecodeto managethem.
Moreover, mobile agentscandealwith non-continuousnetwork connectionand,asa consequence,they
intrinsically suit mobilecomputingsystems.All thesefeaturesareparticularlysuitablein the information
retrieval area[15].
In this paperwe show theadvantagesof the introductionin theMOMIS architectureof intelligentand
mobile software agentsfor the autonomousmanagementand coordinationof the integrationand query
processesoverheterogeneousdatasources.In particular:
– agentscanbeexploitedto managethesourcesin anautonomousandintelligentway;
2
– agents,by moving on thesourcesites,cansave bandwidthanddealwith unstableconnections;
– dependingon thequeriesandon thesourcesite locations,agentsallow to choosethebestoneamong
differentquerystrategies;
– mobileagentswell fit a scenariowhereusers,sourcesor bothcanbemobile.
Theoutlineof this paperis the following: Section2 introducesthearchitectureof thesystemandex-
plainstherolesof theagents.Section3 showshow thesourcesaremanagedandintegrated,by meansof an
examplein theareaof carcatalogues.Section4 presentstherelatedwork. Section5 concludesthepaper
andsketchessomefuturework.
2 The SystemAr chitecture
MOMIS providesa setof techniquesfor thedesignerto facecommonproblemsthatarisewhenintegrating
pre-existinginformationsources,containingbothsemistructuredandstructureddata.Likeotherintegration
projects[1,38], MOMIS followsa“semanticapproach”to informationintegrationbasedontheconceptual
schema,or metadata,of theinformationsources,andonthe � � architecture[30]. In thefollowingwepresent
theextensionof MOMIS by integratingsoftwareagents(bothfixedandmobile)to whichdelegatespecific
tasks(seeFigure1). In therestof thepaperwereferto MOMIS asthenew infrastructureincludingagents.
Theresultingarchitectureis composedby thefollowing components:
1. acommondatamodel, ODM , andthecorrespondingODL language,todescribesourceschemasfor
integrationpurposes.ODM andODL havebeendefinedin MOMIS assubsetof thecorresponding
onesin ODMG, following the proposalfor a standardmediatorlanguagedevelopedby the � � /POB
workinggroup[14]. In addition,ODL introducesnew constructorstosupportthesemanticintegration
process;
2. Wrapperagents, placedovereachsources,translatemetadatadescriptionsof thesourcesinto thecom-
monODL representation,translate(reformulate)a globalqueryexpressedin theOQL 1 querylan-
guageinto queriesexpressedin thesourceslanguagesandexportqueryresultdataset;
3. a Mediator, which is composedof two componentsin its turn: theGlobal SchemaBuilder (GSB)and
the QueryManager (QM). The Global SchemaBuilder componentprocessesandintegratesODL descriptionsreceived from wrapperagentsto derive the integratedrepresentationof the information
sources.The QM componentperformsqueryprocessingandoptimization.Startingfrom eachquery
posedby the useron the Global Schema,the QM generatesOQL queriesthat aresentto wrapper
agentsby exploitingqueryagents, whicharemobileagents.QM automaticallygeneratesthetranslation
of the queryinto a correspondingsetof sub-queriesfor the sourcesandsynthesizesa unified global
answerfor theuser.
3
WordNet
Service level
ODB-Tools
Global SchemaMETADATA REPOSITORY
Data level
Wrapperagent
RelationalSource
QueryManager
MOMIS mediator
UserApplication
creates
IntegrationDesigner
legenda
CORBA Object
User
GUI
Software tools
CORBA interaction
User interaction
ARTEMIS
SI-Designer
Wrapperagent
XMLSource
Wrapperagent
ObjectSource
Wrapperagent
genericSource
Query agents
Fig.1. TheMOMIS systemarchitecture
MOMIS provides the capability of explicitly introducingmany kinds of knowledgefor integration,
suchasintegrity constraints,intra- andinter-sourceintensionalandextensionalrelationships,anddesigner
supplieddomainknowledge.A CommonThesaurus, which hastherole of a sharedontologyof thesource
is built in a semi-automaticway. The CommonThesaurusis a setof intra and inter-schemaintensional
andextensionalrelationships,describingtheknowledgeaboutclassesandattributesof sourcesschemas;it
providesa referenceon which to basetheidentificationof classescandidateto integrationandsubsequent
derivationof theirglobalrepresentation.
MOMIS supportsinformationintegrationin the creationof an integratedview of all sources(Global
Virtual View) in a way automatedasmuchaspossibleandperformsrevision andvalidationof thevarious
kindsof knowledgeusedfor the integration.To this end,MOMIS combinesreasoningcapabilitiesof De-
scriptionLogicswith affinity-basedclusteringtechniques,by exploiting acommonontologyfor thesources
built by usinglexical knowledgefrom WordNet[29,34].
The Global Virtual View is expressedby usingXML standard,to guaranteethe interoperabilitywith
otheropenintegrationsystemprototypes.
1 OQL is asubsetof OQL-ODMG.
4
2.1 The Rolesof the Agents
Theagentsexploitedby our systemaredevelopedin Jade[5], a Java-basedagentplatformwhich enables
alsomobility.
In our architecture,agentshave two mainroles.On theonehand,thewrappersareagentsthatconvert
thesourceinformationandreactto sourcechanges.On theotherhand,theQM exploits mobileagentsto
carryout theretrieval of information.
Whena new sourcehasto beintegratedin MOMIS, a mobileagentmovesto thesitewherethesource
resides.Suchagentchecksthe sourcetype and autonomouslyinstalls the neededdriver to convert the
sourceinformation.Moreover, a fixedagent,calledwrapperagent, is left at this site to presidethesource
(representedby roundedboxesin Figure1). Besidesinteractingwith queryagentsasdescribedlater, the
wrapperagentsmonitorthechangesthatmayoccurin thedatastructureof sources;in fact,theintegration
of a sourceis performedonceat thebeginning,while queriesoccurlater, evenaftera long period,during
which the sourcemay be modified.Whena changeoccursin a source,the correspondingwrapperagent
createsanappropriatemobileagentthatmovesto theMOMIS siteto inform aboutthenew structure,soas
to updatetheGlobalSchema.In thiscase,theautonomyfeatureof agentshelpsin decidinghow to dealwith
theoccurredchanges.This featuremakeoursystemextremelyflexible. In fact,anagent-basedarchitecture
canbeexploitedto addflexibility if themediatorsystemhasto managesemistructuredsources.As stated
previously, semistructureddatarepresentirregular, unknown or often changingstructuresetof data.An
architecturethatis ableto perceivechangesin sourceschemasandthatgivesmechanismsto autonomously
evaluatethetotal impactof a changeover thewholeschema,needslessinteractionswith thedesigner.
Wrapperagent
RelationalSource
QueryManager
Wrapperagent
XMLSource
Wrapperagent
ObjectSource
Query agent
Fig.2. A trip query
5
Wrapperagent
RelationalSource
QueryManager
Wrapperagent
XMLSource
Wrapperagent
ObjectSource
Query agents
Fig.3. A parallelquery
TheQM worksasfollows.Whenauserqueriestheglobalschema,it generatesasetof sub-queriesto be
sentto thesinglesources.To thispurpose,it canexploit oneor morequeryagents, whichmoveto thesource
siteswherethey interactwith thewrapperagents(seethe“moving smiles” in Figure1). TheQM chooses
thenumberof queryagentsto useby a componentthatanalyzeseachquery[3]. In somecases,it is better
to delegatethesearchto a singlequeryagent,which performsa “trip” visiting eachsourcesite:it canstart
from thesourcethatis supposedto reducethefurthersearchesin themostsignificantway, thencontinuesto
visit sourcesites,performingquerieson thebasisof thealready-foundinformation(seeFigure2). In other
cases,sub-queriesarelikely to bequiteindependent,soit is betterto delegateseveralqueryagents,onefor
eachsourcesite:in thisway thesearchesareperformedconcurrentlywith ahighdegreeof parallelism(see
Figure3). In any case,thepeculiarfeaturesof mobileagentsareexploitedandmake theMOMIS searches
suitableto the Internetenvironment.First, by moving locally to the sourcesite,a queryagentpermitsto
significantlysave bandwidth,becauseit is not necessaryto transfera largeamountof data,but thesearch
computationis performedlocally wherethedataresides.Second,MOMIS canqueryalsosourcesthatdo
nothavecontinuousconnections:thequeryagentmovesto thesourcesitewhentheconnectionis available,
performslocally thesearchevenif theconnectionis unstableor unavailable,andthenreturnsto theQM site
assoonastheconnectionis availableagain.Finally, thisfits well mobilecomputing,wheremobiledevices
(which canhostusers,MOMIS, or sources)do not have permanentconnectionswith the fixed network
infrastructure.
As statedabove,agentsmustinteractandcoordinatewith eachotherto accomplishtheir tasks.In par-
ticular, aninteractionthatworthbeingoutlinedis theonebetweenthequeryagentsandthewrapperagents.
6
Whena queryagentarrivesata sitewherea sourceresides,it hasto submitits queryto thewrapperagent,
and,then,to retrieve the results.This interactioncanoccurby usingdifferentprotocols.MOMIS agents
exploit FIPA speechactsto exchangeinformation,andwethink it is thesimplestwaybecauseit enablesto
sendthewrapperagentamessagecontainingthequeryitself. However, it is notobviousthatsuchcommu-
nicationmechanismis allowedon everysite,becauseof securityandlocalizationissues.Anotherpossible
protocolthatwe areevaluatingis basedon a shareddataspaceswhereagentsput andretrieve messages,
uncouplingin this way the interactionsandachieving moreflexibility . See[17] for a comparisonamong
differentkindsof coordinationfor Internetapplicationsbasedonmobileagents;anapproachthatis gaining
groundmoreandmorein theInternet-agentareais theonebasedonprogrammabletuplespaces[16], which
enablecontext-dependentcoordination[19].
2.2 Wrapping semistructuredsources
During the information integration process,many problemsarisedue to structuraland implementation
heterogeneity(includingfor exampledifferencesin hardwareplatforms,DBMS, datalanguages)andfrom
thesemanticheterogeneity, whendifferentnamesareemployedto representthesameinformation(naming
conflicts)or whendifferentmodellingconstructsareusedin differentsourcesto representthesamekind of
information.In the following we explain theapproachadoptedby a wrapperagentto manageinteraction
with thesources.
To managetheimplementationheterogeneity, a mediatorsystemtypically encapsulateseachsourceby
a wrapper, which logically convertsthe underlyingdatastructureto the commondatamodel.Thus, the
wrapperarchitectureandinterfacesarecrucial,for managingthediversityof datasources[38].
In particular, themaintasksof awrappercomponentare:
– during the integrationprocess,the wrappertranslatesthe schemaof a sourceinto the commondata
modelof themediator(in ourapproachby usingthelanguageODL );– during the queryingprocess,the wrapperconvertsqueriesposedover the commondatamodel into
requestssuitablefor the sources,and it convertsdatareturnedby the sourceinto the commondata
model.
For aconventionalstructuredinformationsource(e.g.relationaldatabasesor objectorienteddatabases),
the schemadescriptionis alwaysavailableandcanbe directly translatedinto the selectedcommondata
modelby theavailablewrappers.For example,for objectorienteddatabasesandflat files, MOMIS wrap-
persperformasyntactictranslation,while for relationaldatabasesthetranslationis basedontransformation
rule-sets,asdescribedin [24], to performrelationalto ODMG schemaconversion.For semistructuredin-
formationsources(e.g.,Webdatasources),a schemadescriptionis in generalnot directly availableat the
7
sources;in fact,a basiccharacteristicof semistructureddatais that they are“self-describing”,hencethe
informationassociatedwith theschemais specifiedwithin data [12].
Thus, to integratea semistructuredsource,a specificwrapperhasto implementa (semi)-automatic
methodologyto extract andexplicitly representthe schemaof the source.In [35,13] methodologiesto
extractstructuresfromsemistructureddatafilesareproposed.Moreover, in orderto integratesemistructured
informationsources,wehave to take into accountthatseveraldatamodelsrepresentingthiskind of source
have beenproposedin literature.In particular, theOEM model(ObjectExchangeModel) maybethought
asthe de factomodelto representsemistructureddata.It wasoriginally introducedfor the Tsimmisdata
integrationproject[22].
Following theOEM model,MOMIS representssemistructuredinformationsourcesasrooted,labeled
graphswith the semistructureddata(e.g.,an imageor free-formtext) as nodesand labelson edges.A
semistructuredobject(object,for short)canbeviewedasa triple of theform � id, label, value � ,
whereid is theobjectidentifier, label is a stringdescribingwhat theobjectrepresents,andvalue is
the value,that canbe atomicor complex. An atomicvaluecanbe integer, real, string, image,while the
complex valueis a setof semistructuredobjects,that is, a setof pairs(id,label).A complex objectcanbe
thoughtastheparentof all theobjectsthat form its value(childrenobjects).A givenobjectcanhave one
or moreparents.We denotethe fact that an objectso’ is a child objectof anotherobjectso by so �so’ andusenotationlabel(so) to denotethe label of so. In semistructureddatamodels,labelsare
descriptive asmuchaspossible.Generally, the samelabel is assignedto all objectsdescribingthe same
conceptin a givensource.To representtheschemaof a semistructuredsourceS, we introducethenotion
of objectpattern. All objectsso of S arepartitionedinto disjoint sets,denotedset,suchthat all objects
belongingto thesamesethavethesamelabel.An objectpatternis thenextractedfrom eachsetto represent
all theobjectsin theset.Then,anobjectpatternis representative of all differentobjectsthatdescribethe
sameconceptin agivensemistructuredsource.An objectpatterndescriptionfollowsopenworld semantics
typicalof theDescriptionLogicsapproach[44]. Objectsconformingto a patternsharea commonminimal
structurerepresentedby non-optionalproperties,but canhave furtheradditional(i.e., optional)properties.
In this way, objectsin a semistructureddatasourcecanevolve andaddnew properties,but they will be
retrievedasvalid instancesof thecorrespondingobjectpatternwhenprocessinga query. In thefollowing,
wedescribeanexampleof wrapper, in particular, in chargeof dealingwith XML sources.
A wrapper for XML-based files Accordingto theadopteddatamodel(ODM ), wedevelopedawrapper
to manageXML files. This wrapperaimsto mapthe datamodelof an XML file into the corresponding
objectpatternmodel.Thiswrappercouldbethoughtasthecoreof furtherextensionsthataimatmanaging
otherXML basedfiles,suchasXHTML files.
8
TheExtensibleMarkupLanguage(XML) [43] is a W3C recommendationandit arisesasa language
to describeinformationsourcesby usinga universalformat.Oneof themain goalsof this standardis to
exchangefilesacrosstheInternet.In comparisonwith HTML, XML canbesynthesizedasfollows [40]:
– Theusermaydefinepersonaltagnamesatwill;
– Thestructureof theXML file mayincludetagsnestedto any level;
– A XML file may includea descriptionof its structurefor useby applicationsthat needto perform
structuralvalidation.Thisdefinitionis calledDTD (DocumentTypeDefinition).
In this way, a XML file may be thoughtasself-describinglike a semistructureddatasource.The main
analogieswith ourmodelof a semistructureddatasourcemaybesummarizedasfollows:
– objectpatternattribute ��� XML tag
– objectpattern��� DTD element
– atomicvalueof anobjectpatternattribute ��� PCDATA value
By using this mapping,our wrapperparsesthe DTD associatedto eachwell-formedXML file and
generatesatranslationfromanXML statementintoanODL statement.Thismappingimpliessomecritical
aspectsdueto thelackof semanticsof XML w.r.t. ODL . In particular, themostrelevantare:theorderin
which attributesaredescribedin theDTD, thetranslationof theconceptof attribute from XML language
into ODL language,the poor type systemprovided by XML and the weak semanticsof intra-schema
references.In thelattercase,to avoid lossof informationduringthetranslationprocess,thedesignermaybe
askedto supplyfurtherinformationby a graphicalinterface.XML Schema,a recentW3Cstandard,allows
to expressmoresemanticson structuresanddatatypes,by usinga XML-basedlanguage.Our wrapperis
ableto integrateXML-Schemasourcesgeneratingamoresignificanttranslationin ODL , furthermorethe
wrappercanbeextendedto manageotherXML-basedlanguages(i.e.RDF, XHTML).
3 Integration Process
TheMOMIS approachto performGlobalVirtual View is articulatedin thefollowing phases:
1. Generationof a CommonThesaurus.
TheCommonThesaurusis asetof terminologicalintensionalandextensionalrelationships,describing
intra andinter-schemaknowledgeaboutclassesandattributesof sourcesschemas.We expressintra
andinter-schemaknowledgein form of terminologicalandextensionalrelationships(synonymy, hyper-
nymyandrelationship) betweenclassesand/orattributenames.In thisphase,to extractlexiconderived
relationshipstheWordNetdatabaseis used.
9
<!ELEMENT fiat(car*)>
<!ELEMENT car(name,engine,dimensions,tires,
performance,price)>
<!ELEMENT engine(name,cylinders?,layout?,
capacity_cc?,compression_ratio?,
power_kw, fuel_system)>
<!ELEMENT dimensions(length,width,height,
luggage_capacity)>
<!ELEMENT performance (urban_consumption,
combined_consumption,speed)>
<!ELEMENT name (#pcdata)> ...
Fig.4. Fiatdatabase(fiat)
2. Affinity analysisof classes.
Relationshipsin theCommonThesaurusareusedto evaluatethelevel of affinity betweenclasses,both
intra andinter sources.Theconceptof affinity is introducedto formalizethekind of relationshipsthat
canoccurbetweenclassesfrom theintegrationpointof view. Theaffinity of two classesis established
by meansof affinity coefficientsbasedon classnames,classstructuresandrelationshipsin Common
Thesaurus.
3. Clusteringclasses.
Classeswith affinity in differentsourcesaregroupedtogetherin clustersusinghierarchicalclustering
techniques.Thegoal is to identify theclassesthathave to be integratedsincedescribingthesameor
semanticallyrelatedinformation.
4. Generationof themediatedschema.
Unificationof affinity clustersleadsto theconstructionof thepredictedschema.A classis definedfor
eachcluster, which is representative of all cluster’s classesandis characterizedby the unionof their
attributes.Theglobalschemafor theanalyzedsourcesis composedof all classesderivedfrom clusters,
andis thebasisfor posingqueriesagainstthesources.
3.1 Running Example
In orderto illustratehow theMOMIS approachworks,wewill usethefollowing exampleof integrationin
theCarmanufacturingcatalogs,involving two differentdata-sourcesthatcollectinformationaboutvehicle.
The first data-sourceis theFIAT catalog,containingsemistructuredXML informationaboutcarsof the
Italiancarfactory(seeFigure4).
10
Vehicle(name, length, width, height)
Motor(cod m, type, compression ratio,
KW, lubrification, emission)
Fuel Consumption(name, cod m, drive trains,
city km l, highway km l )
Model(name, cod m, tires, steering, price)
Fig.5. Volkswagendatabase(vw)
Theseconddata-sourceis theVolkswagen database(vw) reportedin Figure5, a relationaldatabase
containinginformationaboutthis kind of car. Both databaseschemataarebuilt by analyzingthewebsite
of this factory.
In the following we introducethe generationof the CommonThesaurusassociatedwith the example
domain,startingfrom thelexiconrelationshipsdefinitionby usingWordnet.
3.2 Generationof a Common Thesaurus
The CommonThesaurusis a set of terminologicalintensionaland extensionalrelationships,describing
intra andinter-schemaknowledgeaboutclassesandattributesof sourcesschemas;it providesa reference
to definethe identificationof classescandidateto integrationand subsequentderivation of their global
representation.In theCommonThesaurus,weexpressknowledgein form of intensionalrelationships(SYN,
BT, NT, andRT) andextensionalrelationships(SYN ����� , BT ����� , andNT ����� betweenclassesand/orattribute
names.
TheCommonThesaurusis constructedthroughanincrementalprocessduringwhich relationshipsare
addedin thefollowing order:
1. schema-derivedrelationships: Intensionalandextensionalrelationshipsholdingat intra-schemalevel.
TheserelationshipsareextractedanalyzingeachODL schemaseparately. In particular, intra-schema
RT relationshipsareextractedfrom the specificationof foreign keys in relationalsourceschemasor
complex attributes(relationships)in objectorienteddatabase.Whenaforeignkey is alsoaprimarykey
bothin theoriginalandin thereferencedrelation,a BT/NT relationshipis extracted.We show themost
significantintra-schemarelationshipautomaticallygeneratedfrom MOMIS:�vw.Model RT vw.vehicle ��vw.Model RT vw.motor ��fiat.engine RT fiat.car �
11
2. lexical-derivedrelationships: Terminologicalrelationshipsholdingat inter-schemalevel areextracted
by by analyzingdifferentsourcesODL schemastogetheraccordingto theWordnetsuppliedontology.
Considerthefiat andthevw sources,themostsignificantlexical relationshipsderivedusingWordNet
arethefollowing:�fiat.car SYN vw.vehicle ��fiat.engine.compression ratio SYN
vw.motor.compression ratio ��fiat.dimension BT vw.vehicle.width �
3. designer-suppliedrelationships: Intensionalandextensionalrelationshipssupplieddirectly by thede-
signer, to capturespecificdomainknowledgeaboutthe sourceschemata.Considerthevw source,in
which themodelentitycanbeconsideredasaspecializationof thevehicleentity. Thisrelationshipcan
not beautomaticallyextractedusingboththelexical andthestructuralapproaches,hencewe supplied
thefollowing relationship:�vw.Model NT fiat.car �
This is a crucial operation,becausethe new relationshipsareforcedto belongto the CommonThe-
saurusandthususedto generatetheglobalintegratedschema.Thismeansthat,if anonsenseor wrong
relationshipis inserted,the subsequentintegrationprocesscanproducea wrong global schema.Our
systemhelpsthe designerin detectingwrong relationshipsby performinga Relationshipsvalidation
stepwith ODB-Tools.Validationis basedon thecompatibilityof domainsassociatedwith attributes.
Referringto theCommonThesaurusresultingfrom our example,we show somesignificantrelation-
ships(for eachrelationship,controlflag [1] denotesa valid relationship,while [0] aninvalid one):�fiat.performance.combined consumption RT�vw.fuel consumption.highway km l � [0]�fiat.dimensions BT vw.vehicle.height � [1]�vw.Model.name RT vw.vehicle.name � [1]
4. inferredrelationships: in thisstepMOMIS performsreasoningabouttheCommonThesaurusrelation-
shipsby exploiting thesubsumptionandinheritancecomputationperformedby ODB-Tools[9]. In the
examineddomainODB-Toolssysteminfersthefollowing relationships:�vw.Model RT fiat.dimensions ��vw.Model NT fiat.engine ��vw.motor NT fiat.car �
All theserelationshipsareaddedto theCommonThesaurusandthusconsideredin thesubsequentphaseof
constructionof GlobalSchema.For a moredetaileddescriptionof theabovedescribedprocesssee[10].
12
Terminologicalrelationshipsdefinedin eachstephold at the intensionallevel by definition.Further-
more,in eachof theabove stepthedesignermay“strengthen”a terminologicalrelationshipsSYN, BT and
NT betweentwo classes� � and � � by establishingthat they hold alsoat theextensionallevel, thusdefin-
ing alsoanextensionalrelationship.Thespecificationof anextensionalrelationship,on onehand,implies
theinsertionof a correspondingintensionalrelationshipin theCommonThesaurusand,on theotherhand,
enablesubsumptioncomputation(i.e., inferredrelationships)andconsistency checkingbetweenthe two
classes� � and � � .
Global Classand Mapping Tables
Startingfrom theoutputof theclustergeneration,wedefine,for eachcluster, aGlobalClassthatrepresents
the mediatedview of all the classesof the cluster. For eachglobal classa set of global attributesand,
for eachof them,the intensionalmappingswith the local attributes(i.e. theattributesof the local classes
belongingto thecluster)aregiven2.
Shortly, we cansaythat the global attributesareobtainedin two steps:(1) Union of the attributesof
all theclassesbelongingto thecluster;(2) Fusionof the“similar” attributes;in this stepredundanciesare
eliminatedin asemi–automaticwaytakinginto accounttherelationshipsstoredin theCommonThesaurus.
For eachglobal classa persistentmapping-tablestoringall the intensionalmappingsis generated;it is a
tablewhosecolumnsrepresentthe set of the local classeswhich belongto the clusterandwhoserows
representtheglobalattributes.
The final stepof the integrationprocessprovidesthe export of the Global Virtual View into a XML
DTD, by addingtheappropriateXML TAGsto representthemappingtablerelationships.Theuseof XML
in thedefinitionof theGlobalVirtual View lets to useMOMIS infrastructurewith otheropenintegration
informationsystemsby theinterchangeof anXML datafile. In addition,theCommonThesaurusis trans-
latedinto XML file, sothatMOMIS mayprovidea sharedontologythatcanbeusedby differentsemantic
ontologylanguages[25,23].
In thereferringexamplethefollowing GlobalClassesaredefined:
– Vehicle:containsthevehicle,model,car sourceclassesandaglobalattributesindicatesthesource
name;
– Engine:containstheengine, motor sourceclasses;
– Performance:containstheperformance, fuel consumption sourceclasses;
– Dimensions:containsthedimensions sourceclass.
2 For a detaileddescriptionof the mappingselectionandof the tool SI-Designerwhich assistthe designerin this
integrationphasesee[6].
13
Dynamic local schemamodification
Now, let supposethata modificationoccursin a localsource,for examplein theFIAT DTD anew element
truck is added:
<!ELEMENT truck(name, engine, dimensions, price, capacity)>
In this casethe local wrapperagent thatresidesat theFIAT sourcecreatesa mobileagentthatgoesto
theMOMIS siteandchecksthepermissionto modify theGlobalSchema:if theagentis enabled,it directly
performstheintegrationphases(i.e. CommonThesaurus, Clustering, MappingGeneration) causedby the
schemamodificationandnotifiesto the Integration Designerits actions.Otherwise,if the agenthasnot
enoughrights,it delegatesthewholeintegrationre-processto theIntegrationDesigner.
In our examplethenew truck elementis insertedby the local wrapperagent in theVehicleGlobal
Classandthemappingis performed.
3.3 The Query Manager Agents
Theuserapplicationinteractswith MOMIS to querytheGlobalVirtual View by usingtheOQL language.
This phaseis performedby the QM componentthat generatesthe OQL queriesfor wrapperagents,
startingfrom aglobalOQL queryformulatedby theuserontheglobalschema.UsingDescriptionLogics
techniques,the QM componentcan generatein an automaticway the translationof the genericOQL queryinto differentsub-query, onefor eachinvolvedlocal source.Thequeryagentsaremobileagentsin
chargeof sendingsuchsub-queriesto thedatasourcesitesandtherethey interactwith the local wrapper
agentsto carry out the queries;thenthey reportthe dataresultto the QM. To achieve the global answer,
theQM hasto mergeeachlocal sub-queryresultreportedby anagentinto a unifieddataset.This process
involvesthe solutionof redundancy andreconciliationproblems,dueto the incompleteandoverlapping
informationavailableon thelocalsources,i.e.ObjectFusion[36].
For example,thequery“retrieve thecarnameandpricefor power levelspresentin every sources”,is
expressedasfollows:
Q: select V1.name, V1.power, V1.price,
from vehicle V1
where 1 <= (select count(*)
from vehicle V2
where V2.power = V1.power
and V2.source <> V1.source)
14
Processingthe above global query would individuateall the local classesinvolved: vw.Vehicle,
vw.Model, vw.Motor, fiat.car, fiat.engine.
TheQM, by thequeryreformulationprocess[10], definesthefollowing local queries(QL1 expressed
by SQLandQL2 by XQuery[39]):
QL1: select M1.name, Motor.KW, M1.price
from vw.Model M1, vw.Motor
where M1.cod_m = Motor.cod_m
QL2: FOR $C in document("fiat.xml")//car
RETURN
<car>
<name>$C/name</name>
<price>$C/price</price>
<kw>$C/engine/power_kw</kw>
</car>
Wrapperagent
FIATSource
QueryManager
Wrapperagent
VWSource
Query agents
Fig.6. Parallelqueriesto two sourceswith thesizeof exchangeddata
Sincethetwo queriesareindependent,theQM couldassigneachoneto aqueryagent,soastheretriev-
ing processis executedin parallelby two agentsthatmove to the two local sources(seeFigure6). After
having performedthequery, eachqueryagentcomesbackto the MOMIS siteandreturnsthe dataresult
15
to theQM, which fusesthetwo data-setobtainingthefinal result(in theexamplethefusionis obtainedby
joining thedata-seton thepowerattribute).Thefinal queryis thefollowing:
QF: select DISTINCT QL1.name, QL1.KW, QL1.price
from QL1, QL2
where QL1.KW = QL2.power_kw
UNION
select DISTINCT QL2.name, QL2.power_kw, QL2.price
from QL1, QL2
where QL1.KW = QL2.power_kw
Let ussupposethateachquery(QL1, QL2) reportsanamountof N Kbytesof dataresultsandthatthe
join queryQF mantainsonly the50%of data(N/2). Thetotal amountof transferreddatais 2 * N Kbytes,
while the”useful” datais N Kbytes.
Wrapperagent
FIATSource
QueryManager
Wrapperagent
VWSource
Query agents
Fig.7. Queryagentinteractionscandecreasethesizeof theexchangeddata
Following amoreautonomousapproach,for thisclassof queries(i.e.,whereafusionof dataderivedby
differentlocal sourcesis necessary)thedataprocessshouldbemovedto thesystemswheresourcesreside
to minimizethedatatransfer. In fact,queryagentscanobtainintermediateresults,which aresentto other
queryagentsto performfusionat thelocal sites(seeFigure7).
For instance,thefollowing servicequeriesusinglocalquerylanguageareadded:
QS1: select DISTINCT Motor.KW
16
from vw.Motor
QS2: FOR $KW in distinct(document("fiat.xml")//car)
RETURN
<kw>$KW</kw>
Theseservicequeriesareexecutedby eachqueryagentsto the local sourcesandthedataresults(con-
tainingonly theavailableenginepower) areexchangedwith theotheragent.Let ussupposethat thedata
amountof theseservicequeriesarenegligible. In eachsinglesourcetheintermediatedatasetis joinedto the
local queriesto obtainthe fusedresult(the join attributesareextractedfrom themappingtablesof which
eachqueryagenthasacopy):
Q1: select DISTINCT QL1.name, QL1.KW, QL1.price
from QL1, QS2
where QL1.KW = QS2.power_kw
Q2: select DISTINCT QL2.name, QL2.power_kw, QL2.price
from QL2, QS1
where QL2.power_kw = QS1.KW
In this way, theunionof Q1 andQ2 resultsarethesameobtainedby thefirst shown approach,while
the datatransferamountwith the MOMIS centralsite is drasticallyreduced,sinceonly the requestdata
aremovedby theagent.Supposingthatashortnegligible message(theservicequeries)betweentheagents
impliesa transferof only the”useful” datato MOMIS, thetotal amountof transferreddatais now aboutN
Kbytes,lessof the2 * N Kbytesof thepreviousapproach.
Moreover, if the sitesof the involved sourcesare“near” (in Internetmetrics)oneeachotherbut are
“distant” from theMOMIS site,onequeryagentthatperformsa trip query(seeFigure8 sidea) requires
only two connectiontransfersbetweendistantsites(oneto go andoneto comeback),while a traditional
client-serverapproachwould requiretwo of suchconnectionsfor each remotesource(seeFigure8 sideb),
thuswastingmorebandwidth.For instance,if anAmericanuserwantto get informationaboutItalian car,
all sourcesitesarelikely to belocatedin Europe,while theMOMIS sitemanagingtherequestis locatedat
theothersideof theAtlantic Ocean.
17
Wrapperagent
FiatSource
QueryManager
Wrapperagent
VWSource
Wrapperagent
RenaultSource
Query agent
Wrapperagent
FiatSource
QueryManager
Wrapperagent
VWSource
Wrapperagent
RenaultSource
Slow connections
Fast connectionsa) b)
Requestsand
replies
Fig.8. Agentapproach(a) vs. traditionalapproach(b)
4 RelatedWork
Although thereareseveral mobile-agentapproachesconcerninginformationretrieval [15,45,3], demon-
stratingthat mobility canbe effectively exploited in distributed informationmanagement,thereare few
agent-basedapproachesin theareaof informationintegration.
A significative work is the MCC InfoSleuth(tm)[37,27]. It is an agent-basedsystemfor information
gatheringandanalysistasksperformedover networksof autonomousinformationsources.A key motiva-
tion of theInfoSleuthsystemis thatrealinformationgatheringapplicationsrequirelong-runningmonitoring
andintegrationof informationatvariouslevelsof abstraction.To thisend,InfoSleuthagentsenablea loose
integrationof technologiesallowing: (1) extractionof semanticconceptsfrom autonomousinformation
sources;(2) registrationandintegrationof semanticallyannotatedinformationfrom differentsources;and
(3) temporalmonitoring,informationrouting,andidentificationof trendsappearingacrosssourcesin the
informationnetwork. Anotherexperienceis theRETSINA multi-agentinfrastructurefor in-context infor-
mationretrieval [41]. In particular, the LARKS descriptionlanguage[42] is definedto realizethe agent
matchmakingprocess(at bothsyntacticandsemanticlevel) by usingseveraldifferentfilters:Context, Pro-
file, Similarity, Signatureand Constraintmatching.Differently from our approach,both InfoSleuthand
18
RETSINA doesnot takeadvantagefrom themobility featureof theagents,whichweconsiderfundamental
in a dynamicanduncertainenvironmentsuchastheInternet.
In the areaof heterogeneousinformationintegration,many projectsbasedon a mediatorarchitecture
have beendeveloped.Themediator-basedTSIMMIS project[22] follows a ‘structural’ approachanduses
aself-describingmodel(OEM) to representheterogeneousdatasources,rulesexpressedin MSL (Mediator
SpecificationLanguage)to enforcesourceintegrationandpatternmatchingtechniquesto performaprede-
finedsetof queriesbasedon a querytemplate.Differently from MOMIS proposal,in TSIMMIS only the
predefinedqueriesmaybeexecutedandfor eachsourcemodificationa manuallymediatorrulesrewriting
mustbeperformed.
In thefollowing wepresentothersystems,whosemaindifferencewith regardto MOMIS is thelackof
a tool aid-supportfor thedesignerin theintegrationprocess.
The GARLIC project[20] builds up on a complex wrapperarchitectureto describethe local sources
with anOO language(GDL), andon thedefinitionof Garlic Complex Objectsto manuallyunify thelocal
sourcesto defineaglobalschema.
The SIMS project[2] proposesto createa global schemadefinition by exploiting the useof Description
Logics (i.e., theLOOM language)for describinginformationsources.Theuseof a globalschemaallows
bothGARLIC andSIMSprojectsto supportall possibleuserquerieson theschemainsteadof apredefined
subsetof them.
TheInformationManifold system[33] providesa sourceindependentandqueryindependentmediator.
Theinputschemaof InformationManifold is asetof descriptionsof thesources.Givenaquery, thesystem
will createaplanfor answeringthequeryusingtheunderlyingsourcedescriptions.Algorithmsto decidethe
usefulinformationsourcesandto generatethequeryplanhave beenimplemented.Theintegratedschema
is definedmainlymanuallyby thedesigner, while in ourapproachit is tool-supported.
Infomaster[28] provides integratedaccessto multiple distributed heterogenousinformationsources
giving the illusion of a centralized,homogeneousinformation system.It is basedon a global schema,
completelymodelledby theuser, andacoresystemthatdynamicallydeterminesanefficientplanto answer
theuser’squeriesby usingtranslationrulesto harmonizepossibleheterogeneitiesacrossthesources.
5 Conclusionsand Future Work
This paperhaspresentedhow a systemfor information integrationcanbe improved by the exploitation
of mobile agents.In particular, agentsare useful in the managementof the sources,which, in an open
anddynamicscenariolike theInternet,canbespreadandcanchangein a uncontrolledway. Themobility
featurepermitsto overcomethelimitationsof thetraditionalapproachesof distributedsystems.
With regardto futurework, wesketchsomeresearchdirections.
19
Thefirst onerelatesto thedynamicintegrationof informationsources.Currently, whena new sourceis
added(or whenis deleted),theMOMIS systemhasto berestarted.Ouraimis to allow sourceintegrationat
runtime,possiblyby exploiting mobileagentsthatsearchfor interestingnew sourcesor checktherequest
of anadministratorto integratehisnew source.Thiswill permitto facethehighdegreeof dynamismof the
Internet.
Then,we areevaluatingwhich further componentsof the systemcanbe modelledasagents,and,in
particular, which onescantake advantagefrom themobility feature.The fact thatsomecomponentsmay
bemobilepermitsto deploy thewholesystemin a moreflexible andadaptableway.
Finally, an areathat is worth to be explored is the interactionbetweenagents,which can occur in
differentwaysandwith differentlanguages.Appropriatelanguagesor interactionmeansshouldbechosen
to grantinteroperabilityandflexibility to agent-basedsystems.Ontheonehand,complex languagesfor the
knowledgeexchangehavebeenproposed[26]; on theotherhand,mobility of agentspromotestheadoption
of simpleanduncoupledcoordinationprotocols[18].
Acknowledgements
Work supportedby ItalianMinistry for UniversityandScienceandTechnologyResearch(MURST)within
theprojectframeworksof “MUSIQUE: Infrastructurefor QoSin WebMultimediaServiceswith Hetero-
geneousAccess”and“D2I: Integration,Warehousing,andMining of HeterogeneousDataSources”and
AgentLink II - Europe’sNetwork of Excellencefor Agent-basedComputing.
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