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knowledge engineer acts as reference to follow.
Other approaches of ontology evaluation would be
to observe the results of application or task where
this ontology is being used. Prozel and Malanka
(2004) proposed the task-based approach for
ontology evaluation but could not be so much
effective, as ontology acts only a backbone and
several other issues of task itself can generate bad
results. Burton-Jones (2004) defined a semiotic
metrics based on different criteria for ontology
assessment for syntactic and lexical/vocabulary
evaluation. Likewise Fox el al. (1998) made a set of
parameters but these are more useful for manual
assessment of quality of ontology. These ontology
evaluation approaches are useful in different
applications, scenarios and environments (2005) and
the choice of a suitable methodology should be
adopted according to the purpose of evaluation and
where that ontology is used.
5 CONCLUSIONS
Ontology driven architecture has revolutionized the
inference system by allowing interoperability
between heterogeneous multi-vendors systems. We
have identified that accurate ontologies free from
errors enable more interoperability, improve the
accuracy of ontology mapping and merging and
lessen human intervention during this process. We
have discussed existing ontological errors, and
identified newer types of errors present in
ontologies. We have concluded that without
identification and removal of these errors the most
desirable goal of ontology mapping and merging
could not be achieved. We have integrated the
overall work about ontology evaluation based on
design principles and anomalies under one
framework. This framework acts as control
mechanism that helps ontologist to build accurate
ontologies that serve best for the desired
applications, provide better reasoning support, lessen
user intervention in efficient ontology merging and
combined use of independently developed online
ontologies can be made possible.
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