IST-2001-34825

IST-2001-34825

SEWASIE final reviewSEWASIE final review meeting meeting

AachenAachen, , March 14,March 14, 200 2005 5

SEWASIE Query ManagementSEWASIE Query Management

Domenico Beneventano - University of Modena and Reggio EmiliaDomenico Beneventano - University of Modena and Reggio Emilia

Maurizio Lenzerini - University “La Sapienza”, RomaMaurizio Lenzerini - University “La Sapienza”, Roma

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IST-2001-34825

Technique for query answering in the Technique for query answering in the context of one Brokering Agentcontext of one Brokering Agent

Domenico BeneventanoDomenico Beneventano

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SummarySummary

The Mechanical scenarioThe Mechanical scenario– Brokering Agent (BA) Ontology, SINode Ontologies, Brokering Agent (BA) Ontology, SINode Ontologies,

Data Source SchemataData Source Schemata

Query ManagementQuery Management– How to write a query?How to write a query?– How to answer a query?How to answer a query? – Final release of the protoype for Query Management Final release of the protoype for Query Management

in the context of one Brokering Agentin the context of one Brokering Agent

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The Mechanical ScenarioThe Mechanical Scenario

Brokering Agent GVV

Mapping m1

SINodeGVVs

Mapping m2

Source Schemata

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ies BA and SINode Ontologies: example of BA and SINode Ontologies: example of

mappingsmappingsSN1.companSN1.companyy

SN2.companySN2.company

COMPANY_IDCOMPANY_ID COMPANY_IDCOMPANY_ID COMPANY_IDCOMPANY_ID

SUBCONTRATSUBCONTRATOROR

SUBCONTRATOSUBCONTRATORR

CAPITAL_STOCCAPITAL_STOCKK


REGIONREGION REGIONREGION REGIONREGION

ADDRESSADDRESS ADDRESSADDRESS ADDRESSADDRESS

......

S1.aziendeS1.aziende S2.companyS2.company

COMPANY_IDCOMPANY_ID IDID COMPANY_IDCOMPANY_ID

REGIONREGION REGIONREGION

SUBCONTRATSUBCONTRATOROR

SUBCONTRATOSUBCONTRATORR

ADDRESSADDRESS INDIRIZZOINDIRIZZO ADDRESSADDRESS

SINode SN2

S1.aziendeS1.aziende(ID,INDIRIZZO,(ID,INDIRIZZO, ... ) ... )

Mapping Table of Company(mapping m2)

BA GVV

Source Schemata

Source Source S1S1 : : TUTTOSTAMPITUTTOSTAMPI

Source Source S2S2: DEFORMAZIONE: DEFORMAZIONE

Mapping Table of SN2.Company (mapping m1)

S2.CompanyS2.Company(COMPANY_ID,(COMPANY_ID, REGION, …)REGION, …)

SINode SN1

S3.companyS3.company

COMPANY_IDCOMPANY_ID COMPANY_IDCOMPANY_ID

REGIONREGION REGIONREGION



ADDRESSADDRESS ADDRESSADDRESS

Source Source S3S3: SUBFORN: SUBFORN

S3.CompanyS3.Company(COMPANY_ID,(COMPANY_ID, ADDRESS, …)ADDRESS, …)

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UNFOLDERLibrarian

SINodeAgent2

SINodeAgent1

EXPANDER

PLAY MAKERBROKERING AGENT

BAOntology

QUERY AGENT

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The Query ManagementThe Query Management

Give me the subcontracting companies in Veneto

with a big capital stock in the plastic and rubber sector

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End-User Query ToolEnd-User Query Tool

The query interface is meant to support a user The query interface is meant to support a user in in formulating a precise queryformulating a precise query – which best – which best captures her/his information needs – even in captures her/his information needs – even in the case of the case of complete ignorancecomplete ignorance of the of the vocabulary of the underlying information vocabulary of the underlying information system holding the datasystem holding the data

The final purpose of the tool is to generate a The final purpose of the tool is to generate a conjunctive queryconjunctive query ready to be executed by the ready to be executed by the evaluation engine associated to the information evaluation engine associated to the information systemsystem

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The role of the Ontology for the End-UserThe role of the Ontology for the End-User

The intelligence of the interface is The intelligence of the interface is drivendriven by an by an ontologyontology describing the domain of the data in the describing the domain of the data in the information systeminformation system

The ontology defines a vocabulary which is The ontology defines a vocabulary which is richerricher than the logical schema of the underlying data, than the logical schema of the underlying data, and it is meant to be closer to the user’s rich and it is meant to be closer to the user’s rich vocabularyvocabulary

The user can exploit the ontology’s vocabulary to The user can exploit the ontology’s vocabulary to formulate the query, and she/he is formulate the query, and she/he is guidedguided by by such a richer vocabulary in order to understand such a richer vocabulary in order to understand how to express her/his information needs more how to express her/his information needs more preciselyprecisely

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Intentional NavigationIntentional Navigation

It helps an It helps an unskilled userunskilled user during query during query formulation, by overcoming problems related formulation, by overcoming problems related with the lack of schema comprehensionwith the lack of schema comprehension

Queries can be specified through an iterative Queries can be specified through an iterative refinement processrefinement process supported by the ontology supported by the ontology

Users may specify their requests using generic Users may specify their requests using generic terms, refine some terms of the query or terms, refine some terms of the query or introduce new terms, and iterate the processintroduce new terms, and iterate the process

Users Users explore and discoverexplore and discover general information general information about the domain, by getting an explicit about the domain, by getting an explicit meaning to a query and to its subparts through meaning to a query and to its subparts through classificationclassification

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UNFOLDERLibrarian

SINodeAgent2

SINodeAgent1

EXPANDER


BAOntology

QUERY AGENT

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The Query ManagementThe Query Management

Give me the subcontracting companies in Veneto

with a big capital stock in the plastic and rubber sector

Query

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WP6: The End-User Query Tool summaryWP6: The End-User Query Tool summary

Technical challengesTechnical challenges– A logic based frameworkA logic based framework– Reasoning supportReasoning support– Use of web standards Use of web standards

InnovationInnovation– A novel query formation paradigmA novel query formation paradigm– The role of the ontologyThe role of the ontology– A linear paradigm for easy query formulationA linear paradigm for easy query formulation– Multi-language supportMulti-language support

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Query Management: functional architectureQuery Management: functional architecture

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ies Query Management: the three main Query Management: the three main

componentscomponents The Query Agent – The Query Agent – coordination of query processingcoordination of query processing

Accepts the query from the End User Query Tool, Accepts the query from the End User Query Tool, interacts with both the BA and the SINode Agents, interacts with both the BA and the SINode Agents, and returns the result to the End User Query Tooland returns the result to the End User Query Tool

Brokering Agent GVV

SINode GVVs

Mapping m2

Source Schemata

The SINode Query Manager – The SINode Query Manager – reformulation w.r.t. m2reformulation w.r.t. m2

One of the modules of the One of the modules of the SINode AgentSINode Agent: : accepts a query and reformulates it according accepts a query and reformulates it according to the semantics of the SINode Ontology, and to the semantics of the SINode Ontology, and returns the result to the Query Agentreturns the result to the Query Agent

Mapping m1

The Playmaker – The Playmaker – reformulation w.r.t. m1reformulation w.r.t. m1

One of the modules of the One of the modules of the Brokering Agent Brokering Agent (BA)(BA): accepts a query and reformulates it : accepts a query and reformulates it according to the semantics of the BA Ontologyaccording to the semantics of the BA Ontology

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The playmaker: EXPANDER + UNFOLDERThe playmaker: EXPANDER + UNFOLDER EXPANDER (by UNIROMA)EXPANDER (by UNIROMA)

– Query expansion : Query expansion : The query is expanded by taking into account the constraints in the BA-GVV: all constraints in the ontology are “compiled in” the expansion, so that the expanded query (EXPQuery) can be processed by ignoring constraints – this is the first technique of this kind in the data integration literature, as all other approaches to GAV (Global as View) data integration are based on just unfolding (which is an incomplete technique in our case!)

– Subquery identificationSubquery identification: : Relevant subqueries (EXPAtoms) are extracted from the expanded query. An EXPAtom is a Single Class Query, i.e., a query on a single Global Class of the BA-GVV.

UNFOLDER (by UNIMO)UNFOLDER (by UNIMO)– Query unfolding: Query unfolding: Each EXPAtom is unfolded by taking into account the

mappings in the BA Ontology, so that it is rewritten w.r.t. the SINode GVVs.

The unfolding is performed on the basis of the full disjunction operator, used to perform Object Fusion. The output is a SQL query (FDQuery) which computes the full disjunction;the atoms of FDQuery (FDAtoms) are Single Class Queries over the SINode GVV

– Resolution FunctionsResolution Functions: : Resolution Functions, to deal with conflicts among Resolution Functions, to deal with conflicts among attributes involved in the query, are individuated attributes involved in the query, are individuated

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UNFOLDERLibrarian

SINodeAgent2

SINodeAgent1

Query

ExpAtoms

EXPANDER


BAOntology

QUERY AGENT

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The playmaker: EXPANDERThe playmaker: EXPANDER

scq1: SELECT CATEGORY_ID FROM Mould_Making scq2: SELECT NAME,COMPANY_ID,CAPITAL_STOCK, REGION,SUBCONTRACTOR,ADDRESS FROM company WHERE CAPITAL_STOCK > 50 AND AND REGION LIKE 'VENETO' AND SUBCONTRACTOR LIKE ’yes’scq3: ...

Query

Expanded Query: EXPQuery

EXPQuery:SELECT r2.NAME,r2.ADDRESS,r2.NATION FROM scq1 r1,scq2 r2,scq3 r3 WHERE r1.CATEGORY_ID=r3.CATEGORY_ID

AND r2.COMPANY_ID=r3.COMPANY_IDUNIONSELECT r2.NAME,r2.ADDRESS,r2.NATION FROM scq4 r1,scq2 r2,scq3 r3 WHERE …UNION …

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UNFOLDERLibrarian

SewasieRepository

Query

ExpAtoms


ExpAtoms Unfolding: FDQuery,FDAtoms, ResFunctions

EXPANDER


BAOntology

QUERY AGENT

Query

FDAtom2: SELECT COMPANY_ID,NAME,REGION, ADDRESS, SUBCONTRACTOR FROM company WHERE ((REGION) like ('VENETO') and (SUBCONTRACTOR) like ('yes'))FDAtom1:

...

Full Disjunction:FDQuery: SELECT * FROM FDAtom1 OUTER JOIN FDAtom1

ON (FDAtom1.COMPANY_ID = FDAtom2.COMPANY_ID)

The playmaker : UNFOLDERThe playmaker : UNFOLDERscq2: SELECT NAME,COMPANY_ID,CAPITAL_STOCK, REGION,SUBCONTRACTOR,ADDRESS FROM company WHERE CAPITAL_STOCK > 50 AND AND REGION LIKE 'VENETO' AND SUBCONTRACTOR LIKE ’yes’

Resolution Function: precedence(${SI-NMAgent2.company.ADDRESS},${SI-NMAgent1.company.ADDRESS})

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L1L2

O1 O O2

Object Fusion: Object IdentificationObject Fusion: Object Identification Object fusion: grouping together information about the same real-

object stored in different sources (SINodes). Merging data from different sources requires different representations

of the same real world object to be identified; this process is called object identification

In our system the object identification problem is solved by defining

Join Conditions among classes of the same Global Class. A Join Condition can be a generic expression, defined by using SQL or external functions.

In this prototype a simple equality condition is implemented. For example:

JC(L1,L2) : L1.COMPANY_ID = L2.COMPANY_ID

JC(L1,L2)

COMPANY_IDCOMPANY_ID ADDRESSADDRESS ......

123123 Via Ugo ..Via Ugo ..

44 VIA Po, 2VIA Po, 2

COMPANY_IDCOMPANY_ID ADDRESSADDRESS ......

44 Via Larga3Via Larga3

234234 Via Verdi9Via Verdi9

L1=SN1.Company

L2 = SN2.Company

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FDG(L1,L2) : select S(L1)ÈS(L2) from L1 outer join L2 on JC(L1,L2)

A global class is expressed by means of the full-disjunction of local classes, that has been recognized as providing a natural semantics for data merging queries

Definition of full-disjunction [Rajarama, Ullman - PODS 1996]

“Computing the natural outerjoin of many relations in a way that preserves all possible connections among facts”

Given a global class G = { L1, L2, …, Ln }, its instance is the full-disjunction of L1, L2, …, Ln (FDG(L1,L2, …, Ln)) computed on the basis of the Join Conditions

Object Fusion: Full DisjunctionObject Fusion: Full Disjunction

COMPANY_IDCOMPANY_ID ADDRESSADDRESS CAP_STOCKCAP_STOCK

123123 Via UgoVia Ugo 5555

44 Via Po, 2Via Po, 2 6565

COMPANY_ICOMPANY_IDD

ADDRESSADDRESS SUBCONTRSUBCONTR

44 Via Larga 3Via Larga 3 YesYes

234234 Via Verdi 9Via Verdi 9 NoNo

L1.COMPANY_IDL1.COMPANY_ID L1.ADDRESSL1.ADDRESS L1.CAP_STOCKL1.CAP_STOCK L2.COMPANY_IL2.COMPANY_IDD

L2.ADDRESSL2.ADDRESS L2.SUBCONTRL2.SUBCONTR


44 Via Po, 2Via Po, 2 6565 44 Via Larga 3Via Larga 3 YesYes

234234 Via Verdi 9Via Verdi 9 NoNo

L1=SN1.Company L2=SN2.Company

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L1

L2 L3

JC(L1,L3)JC(L1,L2)

JC(L2,L3)

Full Disjunction ComputationFull Disjunction Computation

Goal : To compute the Full Disjunction by means of an SQL query

[Rajarama, Ullman - PODS 1996] : There is a natural outerjoin sequence producing the full disjunction if and only if the set of relation schemes forms a connected, acyclic hypergraph.

But, a Global Class with more than 2 local classes is a cyclic hypergraph.

Naive evaluation (actual implementation) – Example n = 3 select * from L1 outer join L2 on JC(L1,L2))

outer join L3 on ( JC(L1,L3) OR JC(L2,L3))

New proposed method : outerjoin pseudo-sequence – Example n = 3select * from (L1 outer join L2 on JC(L1,L2))

outer join (L1 outer join L3 on JC(L1,L3)) on JC(L2,L3)

Implementation of methods proposed in literature

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Object Fusion: Resolution FunctionsObject Fusion: Resolution Functions

COMPANY_IDCOMPANY_ID ADDRESSADDRESS CAP_STOCKCAP_STOCK SUBCONTRSUBCONTR


44 Via Po 2Via Po 2 6565 YesYes

234234 Via VerdiVia Verdi NoNo

Data coming from different SInodes may be inconsistent

Resolution functions: to solve data conflict on an attribute mapped into more than one SINode (instances of the same object coming from different SINodes have different values for local attributes mapped into the same global attribute)

No data conflict : Homogeneous Attribute An example : precedence(L1.ADDRESS,L2.ADDRESS)

L1.COMPANY_IDL1.COMPANY_ID L1.ADDRESSL1.ADDRESS L1.CAP_STOCKL1.CAP_STOCK L2.COMPANY_IL2.COMPANY_IDD

L2.ADDRESSL2.ADDRESS L2.SUBCONTRL2.SUBCONTR


44 Via Po 2Via Po 2 6565 44 Via Larga 3Via Larga 3 YesYes

234234 Via VerdiVia Verdi NoNo

Application of the resolution functions

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Query unfolding: Query unfolding: Local Queries ComputationLocal Queries Computation

1) Constraint Mapping - <Q_L_condition>: constraints of <Q_condition> which can be solved in L are

rewritten w.r.t. L

2) Residual Constraints - <Q_residual_condition>:constraints not included in all local <Q_L_condition>

3) Local Select List - <Q_L_select-list> : attributes of the <select-list> of Q + residual constraints + Join Conditions

An EXPAtom is a Query Q on a Global Class G = { L1, L2, …, Ln }Q = select <Q_select-list> from G

where <Q_condition>

A FDAtom is a Local Query Q on a Local LQ_L = select <Q_L_select-list> from L

where <Q_L_condition>

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An atomic constraint (GA op value) is mapped onto the local class L as:

(MTF[GA][L] op value) if MT[GA][L] is not null and the op

operator is supported into L

true otherwise

An atomic constraint (GA1 op GA2) is mapped onto the local class L as:

(MTF[GA1][L] op MTF[GA2][L]) if MT[GA1][L] and MT[GA2][L] are not null and

the op operator is supported into L

true otherwise

Constraint mapping for Homogeneous AttributeConstraint mapping for Homogeneous Attributess

The current implementation of the prototype assumes that each operator, OP, used in the global query is supported into a local class, i.e. a constraint including OP can be solved in local class.

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scq2: SELECT NAME,COMPANY_ID,CAPITAL_STOCK, REGION,SUBCONTRACTOR,ADDRESS FROM company WHERE CAPITAL_STOCK > 50 AND AND REGION LIKE 'VENETO' AND SUBCONTRACTOR LIKE ’yes’

FDAtom1SELECT COMPANY_ID,NAME,REGION,ADDRESS,SUBCONTRACTOR FROM SN1.company WHERE (REGION like 'VENETO' and SUBCONTRACTOR like 'yes')

Localqueries

Query unfolding exampleQuery unfolding example

Global Query

Global Class: Company = { SN1.Company, SN2.Company}

FDAtom2SELECT COMPANY_ID,NAME,REGION,ADDRESS,SUBCONTRACTOR FROM SN2.company WHERE ( REGION like 'VENETO' and CAPITAL_STOCK > 50 like 'yes')

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UNFOLDERLibrarian

SINodeAgent2

SINodeAgent1

Query

ExpAtoms


ExpAtoms Unfolding: FDQuery,FDAtoms, ResFunctions

EXPANDER


BAOntology

QUERY AGENT

Query

SEWASIE_DB

The Query AgentThe Query Agent

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SINodeAgent2

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EXPANDER


BAOntology

QUERY AGENT

The Query Agent : EXECUTIONThe Query Agent : EXECUTION

1. EXECUTIONFor each FDAtom (Parallel Execution): INPUT: FDAtom MESSAGES: from QA to SINode Agent OUTPUT:

a table storing the FDAtom result in the SEWASIE_DB

EXECUTION

FDAtoms

Answer to FDAtoms

FDAtoms

Answer to FDAtoms

SEWASIE_DB

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SINodeAgent2

SINodeAgent1

EXPANDER


BAOntology

QUERY AGENT

EXECUTION

FUSION

2. FUSION For each EXPATom (Parallel Execution): INPUT : FDAtoms, FDQuery,

Resolution Functions1. Execution of FDQuery

(Full Disjunction of the FDAtoms)2. Application of the Resolution Functions

on the result of previous action OUTPUT:

a view storing the EXPAtom result in the SEWASIE_DB

The Query Agent : FUSIONThe Query Agent : FUSION

SEWASIE_DB

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FUSION: Detailed stepsFUSION: Detailed steps

1) Local queriesFor each local class L, local query over L : Q_L

2) Full Disjunction of the local query answersQ_FD = FDG (Q_L1, …, Q_Ln)

• Resolution Functions applied to Q_FDQ_FD_RES

1) EXPAtom result = select <Q_select-list> from Q_FD_RES where <Q_residual-condition>

An EXPAtom is a Query Q on a Global Class G = { L1, L2, …, Ln }Q = select <Q_select-list>

from Gwhere <Q_condition>

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SINodeAgent1

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EXPANDER


BAOntology

QUERY AGENT

EXECUTION

FUSION

FINAL RESULT

3. FINAL RESULT

INPUT : Output of the FUSION step

1. Execution of the Expanded Query

OUTPUT : Final Query result view stored in the SEWASIE_DB

The Query Agent : FINAL RESULTThe Query Agent : FINAL RESULT

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ies Query Management: main theoretical Query Management: main theoretical

featuresfeatures

Technique for GAV (Global-as-view) data integration Technique for GAV (Global-as-view) data integration system structured in two levelssystem structured in two levels

At each level, the semantics of the schema (BA GVV, At each level, the semantics of the schema (BA GVV, and SINode GVV, respectively) taken into account by a and SINode GVV, respectively) taken into account by a novel technique (query expansion). novel technique (query expansion). First algorithm of First algorithm of this type proved correctthis type proved correct (i.e., sound and complete wrt (i.e., sound and complete wrt the semantics)the semantics)

By virtue of the separation between query expansion By virtue of the separation between query expansion and query rewriting and evaluation, query processing is and query rewriting and evaluation, query processing is polynomial time in data complexity polynomial time in data complexity (i.e., with respect to (i.e., with respect to the size of the data at the sources)the size of the data at the sources)

The Object Fusion problem is dealt with The Object Fusion problem is dealt with a novel a novel technique based on the combination of technique based on the combination of the full the full disjunction operation and the resolution functionsdisjunction operation and the resolution functions

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IST-2001-34825

Technique for query answering in the Technique for query answering in the context of more than one Brokering context of more than one Brokering AgentAgent

Maurizio LenzeriniMaurizio Lenzerini

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ies Problem: Problem: How to answer a query posed to a How to answer a query posed to a

BA ?BA ?

Brokering Agent Ontology

SINode Global View

Data Sources

Mapping

Mapping


SINode Global View

Data Sources

Mapping

Mapping


SINode Global View

Data Sources

Mapping

Mapping

Query

MappingMapping

Mapping

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Peer-to-peer data integrationPeer-to-peer data integration

Query answering in the context of more than Query answering in the context of more than one Brokering Agent can be seen as the problem one Brokering Agent can be seen as the problem of answering queries in a of answering queries in a peer-to-peer data peer-to-peer data integrationintegration system system

– Peer Peer Brokering agent Brokering agent– P2P mapping P2P mapping mapping between BAs mapping between BAs– Peer data source Peer data source SIN node SIN node– Local mapping Local mapping mapping between BA and SIN mapping between BA and SIN

nodenode

One basic problem in P2P data integration is the One basic problem in P2P data integration is the semantics of P2P mappingssemantics of P2P mappings

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Possible formalizations of P2P mappingsPossible formalizations of P2P mappings

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The three main componentsThe three main components

- see also [Franconi&al ‘04]

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Our approachOur approach: : Epistemic logic semanticsEpistemic logic semantics

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Epistemic logic semanticsEpistemic logic semantics

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Example of the epistemic formalizationExample of the epistemic formalization

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The difference between the two semanticsThe difference between the two semantics

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FOL semantics: model 1FOL semantics: model 1

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FOL semantics: model 2FOL semantics: model 2

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Epistemic semanticsEpistemic semantics

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Distributed query answering algorithmDistributed query answering algorithm

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Current and future workCurrent and future work

Algorithm already implementedAlgorithm already implemented

Future work:Future work:– TestingTesting– Dealing with inconsistencyDealing with inconsistency– Dealing with preferencesDealing with preferences

IST-2001-34825

Documents

Transcript of IST-2001-34825