Page 198 - DCAP312_WEB_TECHNOLOGIES_II

Web Technologies-II

Notes
and on the other hand it allows synchronization of product information management utilities
to other core business entities, such as those in customer data integration (CDI).

OWL allows the definition of richer properties and relationships. Object Properties can be
defined as symmetric, functional, inverse functional, or transitive. Object Properties are then
suitable to describe complex relationships among products and between products and other
entities in product information. The expressivity of OWL allows the definition of logical classes
(intersection, union and complement operators), which enables automatic classification for
product items. For instance, new product categories can be defined as the intersection of two
others: smart phones products, which gather characteristics of both PDA and phones, are
a good example. Any product which is simultaneously a PDA and a phone is then a smart
phone. OWL restrictions can define dynamic categories which do not exist in the pre-designed
category hierarchy and are specified by users at query time. It can represent complex and
potentially evolving categories. For example, using Minimum cardinality restriction, it is
possible to define an “outdated products” category which gathers all products replaced by
at least one other product. Items of dynamic categories can be retrieved using OWL ontology
reasoning. Details of RDF representation of PIM can be found in. Since IBM PIM system
currently uses technologies similar to the triple store for storage (item-property-value), we
support SPARQL queries over PIM storage easily by reusing

SPARQL2SQL query translation technologies developed in. The query rewriting method
translates a SPARQL query into a single SQL statement, utilizing well-developed SQL engines
in a most effective manner.

Figure: Conceptual Architecture for SPARQL Queries over the CDI System

The advantages of OWL ontologies for customer information are similar to those for product
information. Representing and discovering various relationships among customers has a very
high value for the CDI, which is enabled by ontology and rule reasoning. Different from
the PIM system, IBM CDI system makes use of object-oriented database schema for storage.
Each entity of the CDI model owns a separate table to store corresponding instances. So,
we need a mapping to link the CDI data with the OWL ontology generated and enriched
from the CDI logical model. We proposed the following conceptual architecture to develop
a POC system for RDF Access to the IBM CDI system. Note that the ontology view in the
bottom right of Figure is in fact a virtual representation of the CDI data in SOR’s schema
form, over which IBM SHER engine for ontological reasoning can work directly. In the future,
we will support SHER engine over a D2RQ like mapping, and thus replace the ontology
Contd...

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