dl'12 mastro at work

Mastro at Work: Experiences onOntology-based Data Access

Domenico Fabio Savo1, Domenico Lembo1,Maurizio Lenzerini1, Antonella Poggi1,

Mariano Rodriguez-Muro2, Vittorio Romagnoli3,Marco Ruzzi1, Gabriele Stella3

1 Sapienza Universitadi Roma

[email protected]

2 Free University ofBozen-Bolzano

[email protected] Banca Monte dei

Paschi di Siena

[email protected]

May, 2010Mastro at Work Savo et. al.

Motivations

DL-Lite OBDA framework

OBDA

Integrated view, semantically richdescription, mapping for concep-tual level and data sources. Ex-ploiting reasoning to overcome in-completeness

Data SourceData Source

Data SourceData Layer

Ontology Semantic Layer

Queries

Mappings

Mastro at Work Savo et. al.

Motivations

DL-Lite OBDA framework

DL-Lite framework for OBDA

Components:

• A family of OntologyLanguages: DL-Lite.

• A mapping technique forrelational databases:Virtual ABoxes

• Promising proposal.

• However, never evaluated in‘the field’.

Data SourceData Source

Data SourceData Layer

Ontology Semantic Layer

Queries

Mappings


Motivations

The domain

• Joint project on OBDA by Banca Monte dei Paschi diSiena (MPS), Free University of Bozen-Bolzano, andSAPIENZA Universita di Roma.

• Clusters of Connected Customers (CCCs)

• Data is used in risk estimation in the process of grantingcredit to bank customers


Motivations

Problems and Solutions

• management is now completely entrusted to the expertof the applications rather than to the domain experts.

• OBDA has been then used for answering queries posed overthe CCCs ontology, not only aimed at easily extractingrelevant information but also to localize inconsistenciesand incompleteness in the data, as well as to devise newdata governance tasks.


Systems


Mastro

The Mastro-OBDA plugin

A DL-Lite reasoner for the OBDA context that is able to take anontology with with mappings to a relational database (defining a‘virtual Abox’) in order to provide the following services:

Features

• Conjunctive Query Answering

• Epistemic Query Answering (EQL)

• Identification Constraints

• Epistemic Constraints


Protege, OBDA and Mastro plugins

Protege 4 and the OBDA Plugin

Features

• Ontology definition

• Datasource and mappingdefinition

• Interaction withOBDA-reasoner (CQs,Epistemic queries, etc.)


Case Study


MPS

Methodology

• Developed the Ontology independently from the source

• Tools used:• interviews• questionnaires• existing documentation

• Developed over a period of 6 months


Ontology

Excerpt of the Ontology

∃inGrouping v Customer

∃inGrouping− v Grouping∃relativeTo v Grouping

∃relativeTo− v CCC

Grouping v ∃inGrouping−

Grouping v ∃relativeTo(functional relativeTo)

(functional inGrouping−)Grouping v δ(timestamp)

JuridicalCCC v CCCJuridicalCCC v δ(timestamp)

∃inMembership v Customer

∃inMembership− v Membership∃hasMembership v CompanyGroup

∃hasMembership− v Memberhip

∃Membership v ∃inMembership−

Memberhip v ∃hasMembership−

(functional inMembership−)(functional hasMembership)

Holding v MembershipMembership v δ(timestamp)

CompanyGroup v δ(id code)

79 concepts, 33 roles, 37concept attributes, 600DL-LiteA,Id axioms


Constraints

IDCs to impose complex business constraints

(id JuridicalCCC timestamp, relativeTo−

◦ inGrouping− ◦ inMembership ◦ ?Holding◦ hasMembership−)

• At the same time two juridical CCCs cannot comprisecustomers that are lead members, i.e., are the holdings, of thesame company group.

A total of 30 Identification Constraints


Constraints

EQLCs to impose complex business constraints

EQLC( verify not exists (

SELECT jurCCC.jccc

FROM sparqltable(SELECT ?jccc

WHERE{ ?jccc rdf:type ’JuridicalCCC’ })jurCCCWHERE jurCCC.jccc NOT IN (

SELECT withGroupLeader.jccc

FROM sparqltable(SELECT ?jccc, ?mem

WHERE{ ?cus rdf:type ’Customer’.

?cus :inMembership ?mem.?mem rdf:type ’Holding’.

?cus :inGrouping ?gr. ?gr :relativeTo ?jccc.

?jccc rdf:type ’JuridicalCCC’}) withGroupLeader ) ) )

• There does not exist a juridical CCC that does not comprise acustomer which is the holding member of a company group

A total of 27 Epistemic Constraint


OBDA Mappings

The Data Source

• Currently, MPS applications managing CCCs rely over a 15million tuple database, stored in 12 relational tables underIBM DB2 RDBMS

Source name Source Description Source sizeGZ0001 Data on customers 3.463.083GZ0002 Data on juridical connections between customers 157.280GZ0003 Data on guarantee connection between customers 1.270.333GZ0004 Data on economical connections between customers 104.033GZ0005 Data on corporation connections between customers 1.021.779GZ0006 Data on patrimonial connections between customers 809.321GZ0007 Data on company groups 55.362GZ0012 Customers loan information 5.966.948GZ0015 Data on monitoring and reporting procedures 1.243GZ0101 Data on membership of customers into CCCs 2.225.466GZ0102 Information on CCCs 663.656GZ0104 Data on bank credit coordinators for juridical CCCs 38.457


OBDA Mappings

OBDA Mappings: Example

SELECT id cluster, timestamp val FROM GZ0102, GZ0007

WHERE GZ0102.validity code = ‘T’ AND GZ0102.id cluster <> 0

AND GZ0007.validity code = ‘T’ AND GZ0007.id group <> 0

AND GZ0102.id cluster = GZ0007.id group

JuridicalCCC(ccc(id cluster, timestamp val)),timestamp(ccc(id cluster, timestamp val), timestamp val)

If the tuple (243, 24052009112341) is in ans(body) the we havethe following Virtual ABox assertions:

JuridicalCCC(gcc(243, 24052009112341))timestamp(gcc(243, 24052009112341)


Experimentation Ontology usage


Ontology usage

Verifying incompleteness in the data through queryanswering

Incompleteness of the data

Querying the database directly vs. querying the ontology providesmore answers.

• To retrieve the identification codes of all company groups.DB operations use id code from GZ0007

• Asking for q(y)← CompanyGroup(x), id code(x , y)

• Mastro indicates that GZ0007 is not the only relevant table.


Ontology usage

Verifying inconsistencies in the data through queryanswering

Inconsistency of the data

Using epistemic query answering to locate inconsistent tuples.

• (functional ingrouping−)• We can detect the violating tuples using:

SELECT testview.l, testview.c1, testview.c2

FROM sparqltable (SELECT ?l ?c1 ?c2

WHERE{?c1:inGrouping?l. ?c2:inGrouping?l}) testview

WHERE testview.c1 <> testview.c2


Query structure

Evaluation Performance


Query structure

Query Performance

Query answering in DL-Lite for OBDA in a nutshell

• Reformulate w.r.t. T• Unfold w.r.t. M• Evaluate

Sources of complexity

• Reformulation - Size of the reformulation

• Unfolding - Size of the unfolding and query structure

Most critical aspect in the MPS scenario: query structure.


Query structure

Query Structure

In Mastro, query unfolding is done by means of partial evaluationand SQL views.

Given a Virtual Abox defined by DB, the mappings M and a queryQ to be evaluated we:

• Define a set of auxiliary predicates and SQL views

• Associate these to T by means of a logic program P• Compute the partial evaluation of Q with respect to P• Translate the PE into SQL by means of the views.


Query structure

Query Structure




• Associate these to T by means of a logic program P

• Compute the partial evaluation of Q with respect to P• Translate the PE into SQL by means of the views.


Query structure

Query Structure




• Associate these to T by means of a logic program P• Compute the partial evaluation of Q with respect to P

• Translate the PE into SQL by means of the views.


Query structure

Query Structure




• Associate these to T by means of a logic program P• Compute the partial evaluation of Q with respect to P• Translate the PE into SQL by means of the views.


Query structure

T -viewsExample:The mappings

m1: SELECT .... WHERE cd tp = 503 ; linkedTo(cus(idcus), link(linkid))m2: SELECT .... WHERE cd tp = 501 ; linkedTo(cus(idcus), link(linkid))

The view for AuxlinkedTo

SELECT ‘cus(’||idcus||‘)’ as term1, ‘link(’||linkid||‘)’ as term2

FROM (SELECT .... WHERE cd\_tp = 503) view\_m1

UNION

SELECT ‘cus’(||idcus||‘)’ as term1, ‘link(’||linkid||‘)’ as term2



Query structure

T -views, unfoldingProgram

linkedTo(x , y)← AuxlinkedTo(x , y)

The queryq(x , y)← linkedTo(x , z), linkedTo(y , z)

The partial evaluation

q(x , y)← AuxleadsTo(x , z),AuxlinkedTo(y , z)


Query structure

T -views, unfolding

SELECT leadsto1.term1, leadsto2.term1 FROM (



UNION



) as leadsto1,

(



UNION



) as leadsto2

WHERE leadsto1.term2 = leadsto2.term2


Query structure

Performance of T -viewsPoor performance, in the order of hours, for trivial queries.

Culprit

Materialization of partial results in the DBMS query plans.

Solution

For relational DBMS queries, simpler is better.


Query structure

M-views

Example:Mappings

m1: SELECT .... WHERE cd tp = 503 ; linkedTo(cus(idcus), link(linkid))m2: SELECT .... WHERE cd tp = 501 ; linkedTo(cus(idcus), link(linkid))

The views:

Auxm1 = SELECT .... WHERE cd tp = 503

Auxm2 = SELECT .... WHERE cd tp = 503


Query structure

M-views, unfolding

Program:

linkedTo(cus(idcus), link(linkid))← Auxm1(idcus, linkid)

linkedTo(cus(idcus), link(linkid))← Auxm2(idcus, linkid)

The queryq(x , y)← linkedTo(x , z), linkedTo(y , z)

The partial evaluation

q(cus(idcus1), cus(idcus2))← Auxm1(idcus1, linkid1),Auxm1(idcus2, linkid1)




Query structure

M-views, unfolding

SELECT ’cus(’||auxm11.idcus||’)’ as x, ’cus(’||auxm12.idcus||’)’ as y

FROM (SELECT .... WHERE cd\_tp = 503) as auxm11,

(SELECT .... WHERE cd\_tp = 503) as auxm12

WHERE auxm11.linkid = auxm12.linkid

UNION





UNION






Query structure

Performance comparison

figures/performances4.pdf


Conclusions

Conclusions


Conclusions

MPS feedback

Useful result from the MPS point of view

• Data Integration

• Data Quality

• Knowledge Sharing

From the technical point of view:

• DBMS level performance for on-the-fly OBDA is possible

• Query tuning is mandatory.

• Pinpointed the features of the queries that are needed forgood performance and those that trigger bad performance.


Conclusions

Current and Future work

• Experiment with live access to the sources

• Extend the current experimentation to other data domains inMPS

Preview of the Mastro OBDA plugin and the OBDA plugin forProtege 4.0

• http://www.dis.uniroma1.it/quonto/

• http://obda.inf.unibz.it


http://www.dis.uniroma1.it/quonto/

http://obda.inf.unibz.it

dl'12 mastro at work

Education

virtual abox

dbms query

views poor

id group juridicalccc

query structure

sql views

id juridicalccc

select id