Databases Reference
In-Depth Information
Fig. 2.8
Screenshot of OLA visualization of an OWL ontology
publicly with sharing in mind. In contrast, schemas are often internal to a particular
application and are not available for others to consume or re-use. In terms of match-
ing, the focus in ontology matching is usually to create semantic links between two
independent ontologies that can later be used for various applications. With data-
specific schemas, data translation or integration is often the focus. Thus, a lot of
schema-matching tools support sophisticated methods for constructing transforma-
tion rules to translate data from a source schema to a target. Finally, while ontology
matching has primarily been confined to research laboratories, there is a number of
commercial tools available for schema matching. Microsoft, IBM, and Oracle are
just a few of the companies that have commercial tools available.
Many of these tools have been developed through successful collaborations
between researchers and industry. Clio, one of the first and most sophisticated
schema matching tools, was a research prototype developed through a collabo-
ration at IBM's Almaden Research Center and the University of Toronto [
Miller
et al.
2001
]. Clio can automatically generate a view to reformulate queries from one
schema to another or transform data from one representation to another to facilitate
data exchange.
Like the previously discussed ontology matching tools, Clio proposes a semi-
automatic approach and supports a visual matching representation similar to
COMA
CC
,C
OG
Z, and OntoMapper (see Fig.
2.10
). Users can draw arrows
