using ontology for improving database utilization this short presentation is merely about the...

Using Ontology for Improving Database Utilization

This short presentation is merely about the benefits of ontology approach for database

applications. It touches upon the issues mentioned during the discussion on the

ONTOLOG.

Tatiana Malyuta

12-Oct-2006 T. Malyuta 2

Ontology for Quality of DataRecently, following the discussion of the most important applications of ontologies on the ONTOLOG, five types of applications have received the highest rating. Among them were the applications dealing with standards and improvement of data quality. Ontology that offers open and standardized description of Database semantics can substantially improve quality of data and data utilization.

Ontology + Database = (Standards + Explicit Semantics) + Database

Improved Data Utilization + Data Quality


Semantics of Data in IS

Database

•Structure•Physical parameters•Limited semantics

File

Application

•Structure

•Physical parameters

•Semantics

•Processing

Application

•Semantics

•Processing

Application

•Processing

Database

•Structure•Physical parameters•Limited semantics

Ontology•Semantics


Semantics of Data

An application traditionally implements semantics of data and data processing, which makes it dependant on data and tightly coupled with it. Databases that support data structure and some limited semantics, loosened the dependency, but not eliminated it.

Extracting semantics from the application and Database into a separate component helps to achieve:

– Explicit and reusable description of the domain that allows for automated data processing and improves quality of data utilization.

– Loose coupling of application and database that improves application’s manageability.


Limited Semantics of DatabaseStructure of data—tables and columns—corresponds to the domain’s main concepts and their properties in ontology.

Relationships between tables (implemented through the foreign key constraint) correspond to properties in ontology.

Additional objects of Database, e.g. views, define additional concepts based on the main concepts and properties.

This limited semantics is enclosed in the database.


Data Integration and HCI

In absence of the explicit semantics, important and common type of applications, like data integration and Human Computer Interface, require human involvement to:

– Establish data structures, formats, etc.– Reconcile data structures, formats, etc.– Implement data processing according to data

structures.

Application


To ease the pain of data integration, continuous modifications of applications caused by changes in structure and semantics of data, and reduce human efforts in building applications and interfaces, today the IS contains metadata repository (usually in XML format).

The repository contains metadata describing data structure, data semantics, application requirements, etc. An example of such repository is Services Descriptions Repository, e.g. UDDI for SOA.

Metadata Component


Metadata in IS

Application

Metadata


Metadata repository offers significant benefits for data utilization due to openness and standard format.

However, metadata (XML) allows to express only limited semantics with the help of data structure and is not supported by inference mechanisms.

Ontology brings to a new level promises of XML technologies. It can further improve properties of database applications.

Metadata vs. Ontology


• Conceptual interaction of Ontology and Database.

• Technological interaction.– Involvement of the reasoner in data access.

• Bridging semantics of Ontology and Database. Methodology of building the “bridge”.

• Mapping the semantics of Ontology into the data model. Methodology of ontology-supported database design.

Discussion in the Mini-Series


Other Mentioned Issues• Using Ontology for Database Design.

Mapping Ontology in the Data Model will help to automate the design process and ensure that the database complies with standardized domain description.

• Concerns about locality of Ontologies built by database professionals.“Think globally, act globally” approach is definitely better than “think locally, act locally” in terms of quality of the result. However, it is usually much worse in terms of ROI and often is unaffordable. A database can benefit even from a “local” ontology. Of course, the global ontologies promise more global benefits.

• Reversed Engineering from Database to Ontology. Limited semantics of Database can be mapped into Ontology, which can be further developed (some vendors provide the tools for this).


SummaryAdding to the IS Ontology—open, standardized, and semantically rich description of the domain that allows for logical inference—promises:

• Automated building and management of database applications, including data integration and Human-Computer Interfaces.

• Standardization of databases.• Better data quality and data utilization.

using ontology for improving database utilization this short presentation is merely about the...

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