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-2006T. Malyuta2 Ontology for Quality of Data Recently, 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

12-Oct-2006T. Malyuta3 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

12-Oct-2006T. Malyuta4 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 applications manageability.

12-Oct-2006T. Malyuta5 Limited Semantics of Database Structure of datatables and columnscorresponds to the domains 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.

12-Oct-2006T. Malyuta6 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

12-Oct-2006T. Malyuta7 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

12-Oct-2006T. Malyuta8 Metadata in IS Application Metadata

12-Oct-2006T. Malyuta9 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

12-Oct-2006T. Malyuta10 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

12-Oct-2006T. Malyuta11 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).

12-Oct-2006T. Malyuta12 Summary Adding to the IS Ontologyopen, standardized, and semantically rich description of the domain that allows for logical inferencepromises: Automated building and management of database applications, including data integration and Human-Computer Interfaces. Standardization of databases. Better data quality and data utilization.