OWLED'12 Quest

A reasoner for Ontology Based Data Access

Mariano Rodríguez-Muro and Diego CalvaneseKRDB Research Group

Free University of Bozen-BolzanoOWLED’12May, 2012

Quest

OBDA and -Quest-

OWL Ontologies

• Uses• Documentation• Knowledge Exchange• Discovering new knowledge• Ontologies + Data…

OBDA and -Quest-

Instance reasoning

• Instance reasoning• Infer new information about the data• Detect inconsistent data• Use inferred information for complex queries (e.g., SPARQL)

• Aim: Large ontologies + Large data• Traditional approach...

OBDA and -Quest-

The usual workflow (ETL)

Reasoner

Source

Application

Communication

Ontology

Inputs

Triples Application Code (e.g., D2RQ, R2RML processors, etc)

OBDA and -Quest-

Problem with approach • Software Complexity• Duplication• Data refreshing

• Performance (implementation, even light languages)• Data structure is lost (PKEYS,

FOREIGN KEYS, etc)

Reasoner

Source

Application

Communication

Ontology

Inputs

Triples Application Code

OBDA and -Quest-

OBDA Models: Sources and Mappings

“A formal specification of the relationship between data in a data source and the vocabulary of the ontology”

OBDA Model

Source Declaration

Source MA set of mappings

Mapping: “A tuple of an source query (e.g., SQL) and a template of the ABox assertions to defined by the answers to the query.”

OBDA and -Quest-

OBDA as an Architecture

Reasoner

Source

Application

Direct Communication

Ontology

OBDA Model

Inputs

OBDA and -Quest-

The Pay-off

OBDA and -Quest-

The Pay-off• At least• The source is documented• Data handling can be done automatically (by the reasoner)• Reduced cost of application development and maintenance• The reasoner can analyze source and mappings to minimize the cost of

inference

OBDA and -Quest-

The Pay-off• At least• The source is documented• Data handling can be done automatically (by the reasoner)• Reduced cost of application development and maintenance• The reasoner can analyze source and mappings to minimize the cost of

inference

• The sweet spot (with OWL 2 QL/RDFS)• On-the-fly ontology based data access• Exploitation of efficient sources (e.g., SQL engines) • Reasoning by pure query rewriting

OBDA and -Quest-

An OBDA reasoner focused on fast and efficient query answering over very large ontologies and very large volumes of data.Features:• Support for RDFS and OWL 2 QL semantics• SPARQL* (> UCQs)• Powerful mapping language (often compensates for OWL 2

QL)• OWLAPI 3 and Protégé 4.1 support• Reasoning by query rewriting.• Relies on SQL engines for query execution.• ABox modes...

Quest

OBDA and -Quest-

Quest in “classic ABox mode” (R/W)

Ontology

Quest

ABox/OBDA Model

Source

Application

JDBC

Storage is is based on the Semantic Index technique (ISWC11, KR12)

Internal DB

OBDA and -Quest-

Quest in “virtual ABox mode” (read-only)

Ontology

Quest

OBDA Model

Source

ApplicationInputs

PostgreSQL, MySQL, SQL Server, DB2 and Oracle

JDBC

OBDA and -Quest-

Data integration with virtual ABox mode

Ontology

Quest

OBDA Model

Database Federation

Application

JDBC

Inputs

E.g., Teiid, Oracle, DB2

OBDA and -Quest-

What’s special about Quest?• We realized that SQL determines performance, not TBox query

rewriting.• Query rewritings in Quest are “natural” SQL queries • Effective query rewriting:• Highly efficient rewriting algorithm• Highly efficient SQL generation:• Detection of redundant SQL (w.r.t. constraints and mappings)• Optimized individual SQL queries (w.r.t. constraints and mappings)• Generates optimal SQL for modern engines

• Beyond academic prototype, focused on features for SW application development.• Going beyond OWL 2 QL. Rules (SWRL, RIF), exploiting

recursivity of SQL and Datalog engines for OWL 2 EL, hybrid approaches for OWL 2 RL.

OBDA and -Quest-

OBDA and -Quest-

THANK YOUQuestions, Examples, Hands-on or Demos?

OBDA and -Quest-

Query Rewriting in a Nutshell

“Given a query Q, a TBox T, an OBDA model <D, M> to compute a query Q’ over D that returns the desired

answers”

OBDA and -Quest-

Example OBDA model

id [PKEY] name age ssn

12 John 37 xxx-999

Table: patient

patient_id [FKEY] c_id [FKEY]

12 33

Table: condition

OBDA and -Quest-

Example OBDA model

SELECT id,name,age,ssn FROM patient

:person/{$id} a Patient; name $name; age $age^^xsd:int; ssn $ssn


12 John 37 xxx-999

Table: patient


12 33

Table: condition

OBDA and -Quest-

Example OBDA model




12 John 37 xxx-999

Table: patient


12 33

Table: condition

SELECT id, c_id FROM condition:person/{$id} affectedBy :cond/{$id}/{$c_id}

OBDA and -Quest-

Example OBDA model




12 John 37 xxx-999

Table: patient


12 33

Table: condition

SELECT id, c_id FROM condition:person/{$id} affectedBy :cond/{$id}/{$c_id}

SELECT id,c_id FROM condition WHERE c_id = 33:cond/{$id}/{$c_id} a CardiacArrest

SELECT id,c_id FROM condition WHERE c_id = 27:cond/{$id}/{$c_id} a Clog

OBDA and -Quest-

Query Rewriting: An example

Ontology (Tbox)

SubClassOf(:CardiacArrest :HearthCondition)SubClassOf(:Clog :HearthCondition)

Query (SPARQL)

SELECT ?p ?n ?ssn WHERE { ?p a :Patient; :name ?n; :ssn ?s; :age ?a; :affectedBy [ a :HeartCondition ]. FILTER (?a >= 21 && ?a <= 50)}

OBDA and -Quest-

Query Rewriting An Example

Rewriting w.r.t. the OBDA model (mappings)

Efficient n-ary to binary!!

OBDA and -Quest-



SELECT (‘http://quest.org/owled#’ || tp.id) as p, tp.name as n, tp.ssn as sFROM patient tp JOIN condition tc ON tp.id = tc.patient_idWHERE (c.c_id = 33 || c.c_id = 27) AND tp.age >= 21 AND tp.age <= 50


OBDA and -Quest-



SELECT (‘http://quest.org/owled#’ || tp.id) as p, tp.name as n, tp.ssn as sFROM patient tp JOIN condition tc ON tp.id = tc.patient_idWHERE (c.c_id = 33 || c.c_id = 27) AND tp.age >= 21 AND tp.age <= 50

p n s

:person/12 John xxx-999

Answer


Technology

OWLED'12 Quest