A Framework for Evaluating Agricultural Ontologies

Anat Goldstein,Gilad Ravid,Lior Fink

doi:10.3390/su13116387

Anat Goldstein, Gilad Ravid + Show 1 more

Open Access

https://doi.org/10.3390/su13116387

Copy DOI

Abstract

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 evaluation methods are applied during the ontology development process. Our work contributes to the literature on agricultural ontologies by presenting a framework that guides the selection of suitable evaluation methods, 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.

Highlights

An ontology is a formal representation of domain knowledge, which can be interpreted by machines [1]
To facilitate the selection of suitable evaluation methods, we propose a framework that links between the ontology purpose, the ontology aspects, and the appropriate evaluation method [44,45]
The evaluation of ontologies with these different purposes requires focusing on different ontology aspects, i.e., it calls for the evaluation of different ontology levels: the lexical, vocabulary, or data level, the hierarchy or taxonomy level, the semantic relations level, and the context level [44]

Summary

Introduction

An ontology is a formal representation of domain knowledge, which can be interpreted by machines [1]. Ontologies formally define the entities (concepts) of a domain, their attributes and the relationships among them, in a machine interpretable way. Ontologies can be used for several purposes: First, an ontology can be used by machines for knowledge deduction [2]. Ontologies enable reuse of domain knowledge [5,6]. Once an ontology is published, it can be used by various applications in various domains. The web-based application and the experiment parts of a domain can be integrated to create one large ontology of the domain [5]. This, may require mappings between concepts of the different ontologies to bridge over different perspectives of the integrated knowledge models.

Methods

Results

Conclusion