Querying Ontology Based Database Using OntoQL Stephane 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  2 E1 ) 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: C  EXTENT 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, I C, 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

OntoQL Extension 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 Features Path 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.