Querying Ontology Based Database Using

OntoQLStephane Jean et al.

Presented by: Meher Talat Shaikh

Overview

OntoQL is a language for defining, manipulating and querying data stored in an OBDB.

Objective: retrieve definition, meaning, translation and/or identifier of a given data item.

OBDB (OntoDB) data model: created and customized by users

OntoQL operators that makes up OntoAlgebra

Example queries

OBDB data model

Built on top of relational database model.

Both the ontology and the instances are kept in the same database.

Content part: Stores the instances

Ontology part: Stores ontology definitions

Ontology

E is a set of entities representing the ontology model

OC is the set of concepts of ontologies

A is the set of attributes describing each OC

SuperEntities: associates set of super entities to an entity (E 2E1 )

TypeOf: Associates the strongest entity to each concept of ontology (OC E)

AttributeDomain, AttributeRange

Val

Ontology kernel

Ontology example

Ontology class example

Content

EXTENT is a set of extensional definitions of ontology classes

I is the set of instances of the OBDB

TypeOf : I EXTENT

SchemaProp : EXTENT 2P

Val

Content cont..

Relationship between ontology and content is defined by

partial function nomination: CEXTENT

Classes without extensional definition are said to be abstract

Content example

Onto Algebra

OntoImage: returns collection of objects after applying a specific function. OntoImage(C, IC, p)

OntoProject: allows the application of more than one function.

OntoSelect: creates a collection of objects satisfying a selection predicate.

OntoJoin: creates relationships between objects of two collections.

* : introduces polymorphism: returns the instances of the class C and all the classes subsumed by C

OntoQLExtension of SQL

DDL

to create, alter and drop concepts of ontologies

to create, alter and drop attributes of these concepts of ontologies

DML

Update, Insert, Delete etc.

OntoQL DDL

Laboratory example

Querying OBDB

example queries

OntoQL FeaturesPath expressions. Associations may be traversed using dot

notation.

Polymorphic query: * operator

Nested queries

Aggregate functions: count, avg, min max.

Quantification: Existential (ANY, SOME) and universal (ALL)

Set operators: Union, Intersection and Except

Processing of ONtoQL OntoQL query is parsed into an OntoAlgebra expression tree

path expressions and * operators removed

The expression tree is optimized

OntoAlgebra is translated to relational algebra tree.

The relational algebra tree is optimized.

The optimized relational algebra trees are translated into SQL queries.

Advantages of OntoQL

Based on SQL

Allows schema manipulation

Express queries in different languages.

Provides GROUP BY and ORDER By operators.

Shortcomings

FROM Clause is mandatory

Does not yet support multi-instantiation capability

Large sets of data are to be evaluated to study the OntoQL scalability issue.

Conclusion

OntoQL is effective in querying data, ontology and both

Based on Object oriented concepts and RDB model

conceptual model may be created and customized by users.

Thank you.