  An ontology is a formal representation of domain knowledge, which can be
interpreted by machines. In recent years, ontologies have become a major tool
for domain knowledge representation and a core component of many knowledge
management systems, decision support systems and other intelligent systems,
inter alia, in the context of agriculture. A review of the existing literature
on agricultural ontologies, however, reveals that most of the studies, which
propose agricultural ontologies, are lacking an explicit evaluation procedure.
This is undesired because without well-structured evaluation processes, it is
difficult to consider the value of ontologies to research and practice.
Moreover, it is difficult to rely on such ontologies and share them on the
Semantic Web or between semantic aware applications. With the growing number of
ontology-based agricultural systems and the increasing popularity of the
Semantic Web, it becomes essential that such development and evaluation methods
are put forward to guide future efforts of ontology development. Our work
contributes to the literature on agricultural ontologies, by presenting a
method for evaluating agricultural ontologies, which seems to be missing from
most existing studies on agricultural ontologies. The framework supports the
matching of appropriate evaluation methods for a given ontology based on the
ontology's purpose.
